Game theoretic prioritization scheme for mobile ad hoc networks permitting hierarchal deference

[0001] The present application claims benefit of priority from U. S. Provisional Patent Application No. 60/609,070, filed Sep. 10, 2004.

[0002] The present invention relates to the field of ad hoc network protocols and control architectures.

[0003] A number of fields of endeavor are relevant to the present invention, and exemplary prior art, incorporated herein by reference, are disclosed below. The references disclosed provide a skilled artisan with embodiments of elements of the present invention, and the teachings therein may be combined and subcombined in various manners in accordance with the present teachings. The topical headings are advisory only, and are not intended to limit the applicability of any reference. While some embodiments are discussed as being preferred, it should be understood advantages or not, form a part of the invention and may be combined and/or subcombined in a consistent manner in accordance with the teachings hereof.

[0004] Internet

[0005] The Internet is structured such various networks are interconnected, with communications effected by addressed packets conforming to a common protocol. Based on the packet addressing, information is routed from source to destination, often through a set of networks having multiple potential pathways. The communications medium is shared between all users. Statistically, some proportion of the packets are extraordinarily delayed, or simply lost. Therefore, protocols involving communications using these packets include error detection schemes that request a retransmit of required data not received within a time window. In the even that the network nears capacity or is otherwise subject to limiting constraint, the incidence of delayed or lost packets increases, thereby increasing requests for retransmission and retransmission. Therefore, as the network approaches available bandwidth, the load increases, ultimately leading to failure. In instances where a minimum quality of service must be guaranteed, special Internet technologies are required, to reserve bandwidth or to specify network pathways. End-to-end quality of service guarantees, however, may exceed the cost of circuit switched technologies, such as dialup modems, especially where the high quality needs are intermittent.

[0006] Internet usage typically involves an Internet server, an automated system capable of responding to communications received through the Internet, and often communicating with other systems not directly connected to the Internet. The server typically has relatively large bandwidth to the Internet, allowing multiple simultaneous communications sessions, and usually supports the hypertext transport protocol (HTTP), which provides, in conjunction with a so-called web browser on a remote client system, a human readable interface which facilitates navigation of various resources available in the Internet. The client systems are typically human user interfaces, which employ a browser to display HTTP “web pages”. The browser typically does not provide intelligence. Bandwidth between the client and Internet is typically relatively small, and various communications and display rendering considered normal. Typically, both client and server are connected to the Internet through Internet service providers, each having its own router.

[0007] It is also known to provide so-called proxy servers and firewalls, which are automated systems that insulate the client system from the Internet. Further, so-called Internet applications and applets are known which provide local intelligence at the client system. Further, it is known to provide a local server within the client system for locally processing a portion of the information. These local servers, applications and applets are non-standard, and thus require special software to be available locally for execution.

[0008] Thus, the Internet poses a number of advantages for commercial use, including low cost and ubiquitous connectivity. Therefore, it is desirable to employ standard Internet technologies while achieving sufficient quality communications to effect an efficient transaction.

[0009] A widely dispersed network of access points may implement a mobile telecommunications protocol, such as IETF RFC 3344 (Mobile IP, IPv4), or various mobile ad hoc network (MANET) protocols, 2.5 G or 3 G cellular, or other types of protocols. Preferably, the protocol allows the client to maintain a remote connection while traversing between various access points. See, U.S. Pub. application No. 20040073642, expressly incorporated herein by reference. Mobile Internet Protocol (Mobile IP or MIP, in this case, v4) is an Internet Engineering Task Force (IETF) network layer protocol, specified in RFC-3344. It is designed to allow seamless connectivity session maintenance under TCP (Transmission Control Protocol) or other connection oriented transport protocols when a mobile node moves from one IP subnet to another. MIPv4 uses two network infrastructure entities, a Home Agent (HA) and an optional Foreign Agent (FA), to deliver packets to the mobile node when it has left its home network. MIPv4 also supports point-of-attachment Care-of Addresses (CoA) if a FA is unavailable. Mobile IP is increasingly being deployed for 2.5/3 G (2.5 or third generation wireless) provider networks and may be deployed in medium and large Enterprise IEEE 802.11 -based LANs (Local Area Networks) with multiple subnets. MIPv4 relies on the use of permanently assigned “home” IP addresses to help maintain connectivity when a mobile device connects to a foreign network. On the other hand, IPsec-based (Internet Protocol Security, a security protocol from IETF) VPNs (Virtual Private Networks) use a tunneling scheme in which the outer source IP address is based on a CoA at the point-of-attachment and an inner source IP address assigned for the “home” domain. In general if either address is changed, such as when the mobile node switches IP subnets, then a new tunnel is negotiated with new keys and several round trip message exchanges. The renegotiation of the tunnel interferes with seamless mobility across wired and wireless IP networks spanning multiple IP subnets.

[0010] Market Economy Systems

[0011] In modem retail transactions, predetermined price transactions are common, with market transactions, i.e., commerce conducted in a setting which allows the transaction price to float based on the respective valuation allocated by the buyer(s) and seller(s), often left to specialized fields. While interpersonal negotiation is often used to set a transfer price, this price is often different from a transfer price that might result from a best-efforts attempt at establishing a market price. Assuming that the market price is optimal, it is therefore assumed that alternatives are sub optimal. Therefore, the establishment of a market price is desirable over simple negotiations.

[0012] One particular problem with market-based commerce is that both seller optimization and market efficiency depend on the fact that representative participants of a preselected class are invited to participate, and are able to promptly communicate, on a relevant timescale, in order to accurately value the goods or services and make an offer. Thus, in traditional market-based system, all participants are in the same room, or connected by a high quality telecommunications link. Alternately, the market valuation process is prolonged over an extended period, allowing non-real time communications of market information and bids. Thus, attempts at ascertaining a market price for non-commodity goods can be subject to substantial inefficiencies, which reduce any potential gains by market pricing. Further, while market pricing might be considered “fair”, it also imposes an element of risk, reducing the ability of parties to predict future pricing and revenues. Addressing this risk may also reduce efficiency of a market-based system.

[0013] Auction Systems

[0014] When a single party seeks to sell goods to the highest valued purchaser(s), to establish a market price, the rules of conduct typically define an auction. Typically, known auctions provide an ascending price or descending price over time, with bidders making offers or ceasing to make offers, in the descending price or ascending price models, respectively, to define the market price. After determining the winner of the auction, the pricing rules define uniform price auctions, wherein all successful bidders pay the lowest successful bid, second price auctions wherein the winning bidder pays the amount bid by the next highest bidder, and pay-what-you-bid auctions. The pay-what-you-bid auction is also known as a discriminative auction while the uniform price auction is known as a non-discriminative auction. In a second-price auction, also known as a Vickrey auction, the policy seeks to create a disincentive for speculation and to encourage bidders to submit bids reflecting their true value for the good. In the uniform price and second price schemes, the bidder is encourages to disclose the actual private value to the bidder of the good or service, since at any price below this amount, there is an excess gain to the buyer, whereas by withholding this amount the bid may be unsuccessful, resulting in a loss of the presumably desirable opportunity. In the pay-what-you-bid auction, on the other hand, the buyer need not disclose the maximum private valuation, and those bidders with lower risk tolerance will bid higher prices. See, www.isoc.org/inet98/proceedings/3b/3b_—3.html; www.ibm.com/iac/reports-technical/reports-bus-neg-internet.html.

[0015] Two common types of auction are the English auction, which sells a single good to the highest bidder in an ascending price auction, and the Dutch auction, in which multiple units are available for sale, and in which a starting price is selected by the auctioneer, which is successively reduced, until the supply is exhausted by bidders (or the minimum price/final time is reached), with the buyer(s) paying the lowest successful bid. The term Dutch auction is also applied to a type of sealed bid auction. In a multi-unit live Dutch auction, each participant is provided with the current price, the quantity on hand and the time remaining in the auction. This type of auction, typically takes place over a very short period of time and there is a flurry of activity in the last portion of the auction process. The actual auction terminates when there is no more product to be sold or the time period expires.

[0016] In selecting the optimal type of auction, a number of factors are considered. In order to sell large quantities of a perishable commodity in a short period of time, the descending price auctions are often preferred. For example, the produce and flower markets in Holland routinely use the Dutch auction (hence the derivation of the name), while the U.S. Government uses this form to sell its financial instruments. The format of a traditional Dutch auction encourages early bidders to bid up to their “private value”, hoping to pay some price below the “private value”. In making a bid, the “private value” becomes known, helping to establish a published market value and demand curve for the goods, thus allowing both buyers and sellers to define strategies for future auctions.

[0017] In an auction, typically a seller retains an auctioneer to conduct an auction with multiple buyers. (In a reverse auction, a buyer solicits the lowest price from multiple competing vendors for a desired purchase). Since the seller retains the auctioneer, the seller essentially defines the rules of the auction. These rules are typically defined to maximize the revenues or profit to the seller, while providing an inviting forum to encourage a maximum number of high valued buyers. If the rules discourage high valuations of the goods or services, or discourage participation by an important set of potential bidders, then the rules are not optimum. A rule may also be imposed to account for the valuation of the good or service applied by the seller, in the form of a reserve price. It is noted that these rules typically seek to allocate to the seller a portion of the economic benefit that would normally inure to the buyer, creating an economic inefficiency. However, since the auction is to benefit the seller, not society as a whole, this potential inefficiency is tolerated. An optimum auction thus seeks to produce a maximum profit (or net revenues) for the seller. An efficient auction, on the other hand, maximizes the sum of he utilities for the buyer and seller. It remains a subject of academic debate as to which auction rules are most optimum in given circumstances; however, in practice, simplicity of implementation may be a paramount concern, and simple auctions may result in highest revenues; complex auctions, while theoretically more optimal, may discourage bidders from participating or from applying their true and full private valuation in the auction process.

[0018] Typically, the rules of the auction are predefined and invariant. Further, for a number of reasons, auctions typically apply the same rules to all bidders, even though, with a priori knowledge of the private values assigned by each bidder to the goods, or a prediction of the private value, an optimization rule may be applied to extract the full value assigned by each bidder, while selling above the sellers reserve.

[0019] In a known ascending price auction, each participant must be made aware of the status of the auction, e.g., open, closed, and the contemporaneous price. A bid is indicated by the identification of the bidder at the contemporaneous price, or occasionally at any price above the minimum bid increment plus the previous price. The bids are asynchronous, and therefore each bidder must be immediately informed of the particulars of each bid by other bidders.

[0020] In a known descending price auction, the process traditionally entails a common clock, which corresponds to a decrementing price at each decrement interval, with an ending time (and price). Therefore, once each participant is made aware of the auction parameters, e.g., starting price, price decrement, ending price/time, before the start of the auction, the only information that must be transmitted is auction status (e.g., inventory remaining).

[0021] As stated above, an auction is traditionally considered an efficient manner of liquidating goods at a market price. The theory of an auction is that either the buyer will not resell, and thus has an internal or private valuation of the goods regardless of other's perceived values, or that the winner will resell, either to gain economic efficiency or as a part of the buyers regular business. In the later case, it is a general presumption that the resale buyers are not in attendance at the auction or are otherwise precluded from bidding, and therefore that, after the auction, there will remain demand for the goods at a price in excess of the price paid during the auction. Extinction of this residual demand results in the so-called “winner's curse”, in which the buyer can make no profit from the transaction during the auction. Since this detracts from the value of the auction as a means of conducting profitable commerce, it is of concern to both buyer and seller. In fact, experience with initial public offerings (IPOs) of stock through various means has demonstrated that by making stock available directly to all classes of potential purchasers, latent demand for a new issue is extinguished, and the stock price is likely to decline after issuance, resulting in an IPO which is characterized as “unsuccessful”. This potential for post IPO decline tempers even initial interest in the issue, resulting in a paradoxical decline in revenues from the vehicle. In other words, the “money on the table” resulting from immediate retrading of IPO shares is deemed a required aspect of the IPO process. Thus, methods that retain latent demand after IPO shares result in post IPO increases, and therefore a “successful” IPO. Therefore, where the transaction scheme anticipates demand for resale after the initial distribution, it is often important to assure a reasonable margin for resellers and limitations on direct sale to ultimate consumers.

[0022] Research into auction theory (game theory) shows that in an auction, the goal of the seller is to optimize the auction by allocating the goods inefficiently, and thus to appropriate to himself an excess gain. This inefficiency manifests itself by either withholding goods from the market or placing the goods in the wrong hands. In order to assure for the seller a maximum gain from a misallocation of the goods, restrictions on resale are imposed; otherwise, post auction trading will tend to undue the misallocation, and the anticipation of this trading will tend to control the auction pricing. The misallocation of goods imposed by the seller through restrictions allow the seller to achieve greater revenues than if free resale were permitted. It is believed that in an auction followed by perfect resale, that any mis-assignment of the goods lowers the seller's revenues below the optimum and likewise, in an auction market followed by perfect resale, it is optimal for the seller to allocate the goods to those with the highest value. Therefore, if post-auction trading is permitted, the seller will not benefit from these later gains, and the seller will obtain sub optimal revenues.

[0023] These studies, however, typically do not consider transaction costs and internal inefficiencies of the resellers, as well as the possibility of multiple classes of purchasers, or even multiple channels of distribution, which may be subject to varying controls or restrictions, and thus in a real market, such theoretical optimal allocation is unlikely. In fact, in real markets the transaction costs involved in transfer of ownership are often critical in determining a method of sale and distribution of goods. For example, it is the efficiency of sale that motivates the auction in the first place. Yet, the auction process itself may consume a substantial margin, for example 1-15% of the transaction value. To presume, even without externally imposed restrictions on resale, that all of the efficiencies of the market may be extracted by free reallocation, ignores that the motivation of the buyer is a profitable transaction, and the buyer may have fixed and variable costs on the order of magnitude of the margin. Thus, there are substantial opportunities for the seller to gain enhanced revenues by defining rules of the auction, strategically allocating inventory amount and setting reserve pricing.

[0024] Therefore, perfect resale is but a fiction created in auction (game) theory. Given this deviation from the ideal presumptions, auction theory may be interpreted to provide the seller with a motivation to misallocate or withhold based on the deviation of practice from theory, likely based on the respective transaction costs, seller's utility of the goods, and other factors not considered by the simple analyses.

[0025] A number of proposals have been made for effecting auction systems using the Internet. These systems include consumer-to-consumer, business-to-consumer, and business-to-business types. Generally, these auctions, of various types and implementations discussed further below, are conducted through Internet browsers using hypertext markup language (HTML) “web pages”, using HTTP. In some instances, such as BIDWATCH, discussed further below, an application with associated applets is provided to define a user interface instead of HTML.

[0026] As stated above, the information packets from the transaction server to client systems associated with respective bidders communicate various information regarding the status of an interactive auction during the progress thereof. The network traffic from the client systems to the transaction server is often limited to the placement of bids; however, the amount of information required to be transmitted can vary greatly, and may involve a complex dialogue of communications to complete the auction offer. Typically, Internet based auction systems have scalability issues, wherein economies of scale are not completely apparent, leading to implementation of relatively large transaction server systems to handle peak loads. When the processing power of the transaction server system is exceeded, entire system outages may occur, resulting in lost sales or diminished profits, and diminished goodwill.

[0027] In most Internet auction system implementations, there are a large quantity of simultaneous auctions, with each auction accepting tens or hundreds of bids over a timescale of hours to days. In systems where the transaction volume exceeds these scales, for example in stock and commodity exchanges, which can accommodate large numbers of transactions per second involving the same issue, a private network, or even a local area network, is employed, and the public Internet is not used as a direct communications system with the transaction server. Thus, while infrastructures are available to allow successful handling of massive transaction per second volumes, these systems typically avoid direct public Internet communications or use of some of its limiting technologies. The transaction processing limitations are often due to the finite time required to handle, e.g., open, update, and close, database records.

[0028] In business-to-business auctions, buyers seek to ensure that the population of ultimate consumers for the good or services are not present at the auction, in order to avoid the “winner's curse”, where the highest bidder in the auction cannot liquidate or work the asset at a profit. Thus, business-to-business auctions are distinct from business-to-consumer auctions. In the former, the optimization by the seller must account for the desire or directive of the seller to avoid direct retail distribution, and instead to rely on a distribution tier represented in the auction. In the latter, the seller seeks maximum revenues and to exhaust the possibilities for downstream trade in the goods or services. In fact, these types of auctions may be distinguished by various implementing rules, such as requiring sales tax resale certificates, minimum lot size quantities, preregistration or qualification, support or associated services, or limitations on the title to the goods themselves. The conduct of these auctions may also differ, in that consumer involvement typically is permissive of mistake or indecision, while in a pure business environment professionalism and decisiveness are mandated.

[0029] In many instances, psychology plays an important role in the conduct of the auction. In a live auction, bidders can see each other, and judge the tempo of the auction. In addition, multiple auctions are often conducted sequentially, so that each bidder can begin to understand the other bidder's patterns, including hesitation, bluffing, facial gestures or mannerisms. Thus, bidders often prefer live auctions to remote or automated auctions if the bidding is to be conducted strategically.

[0030] Internet Auctions

[0031] On-line electronic auction systems which allow efficient sales of products and services are well known, for example, EBAY.COM, ONSALE.COM, UBID.COM, and the like. Inverse auctions that allow efficient purchases of product are also known, establishing a market price by competition between sellers. The Internet holds the promise of further improving efficiency of auctions by reducing transaction costs and freeing the “same time-same place” limitations of traditional auctions. This is especially appropriate where the goods may be adequately described by text or images, and thus a physical examination of the goods is not required prior to bidding.

[0032] In existing Internet systems, the technological focus has been in providing an auction system that, over the course of hours to days, allow a large number of simultaneous auctions, between a large number of bidders to occur. These systems must be scalable and have high transaction throughput, while assuring database consistency and overall system reliability. Even so, certain users may selectively exploit known technological limitations and artifacts of the auction system, including non-real time updating of bidding information, especially in the final stages of an auction.

[0033] Because of existing bandwidth and technological hurdles, Internet auctions are quite different from live auctions with respect to psychological factors. Live auctions are often monitored closely by bidders, who strategically make bids, based not only on the “value” of the goods, but also on an assessment of the competition, timing, psychology, and progress of the auction. It is for this reason that so-called proxy bidding, wherein the bidder creates a preprogrammed “strategy”, usually limited to a maximum price, are disfavored. A maximum price proxy bidding system is somewhat inefficient, in that other bidders may test the proxy, seeking to increase the bid price, without actually intending to purchase, or contrarily, after testing the proxy, a bidder might give up, even below a price he might have been willing to pay. Thus, the proxy imposes inefficiency in the system that effectively increases the transaction cost.

[0034] In order to address a flurry of activity that often occurs at the end of an auction, an auction may be held open until no further bids are cleared for a period of time, even if advertised to end at a certain time. This is common to both live and automated auctions. However, this lack of determinism may upset coordinated schedules, thus impairing efficient business use of the auction system.

[0035] In order to facilitate management of bids and bidding, some of the Internet auction sites have provided non-Hypertext Markup Language (HTML) browser based software “applet” to track auctions. For example, ONSALE.COM has made available a Marimba Castanet® applet called Bidwatch to track auction progress for particular items or classes of items, and to facilitate bidding thereon. This system, however, lacks real-time performance under many circumstances, having a stated refresh period of 10 seconds, with a long latency for confirmation of a bid, due to constraints on software execution, quality of service in communications streams, and bid confirmation dialogue. Thus, it is possible to lose a bid even if an attempt was made prior to another bidder. The need to quickly enter the bid, at risk of being too late, makes the process potentially error prone.

[0036] Proxy bidding, as discussed above, is a known technique for overcoming the constraints of Internet communications and client processing limitations, since it bypasses the client and telecommunications links and may execute solely on the host system or local thereto. However, proxy bidding undermines some of the efficiencies gained by a live market.

[0037] U.S. Pat. No. 5,890,138 to Godin, et al. (Mar. 30, 1999), expressly incorporated herein by reference in its entirety, relates to an Internet auction system. The system implements a declining price auction process, removing a user from the auction process once an indication to purchase has been received. See, Rockoff, T. E., Groves, M.; “Design of an Internet-based System for Remote Dutch Auctions”, Internet Research, v 5, n 4, pp. 10-16, MCB University Press, Jan. 01, 1995.

[0038] A known computer site for auctioning a product on-line comprises at least one web server computer designed for serving a host of computer browsers and providing the browsers with the capability to participate in various auctions, where each auction is of a single product, at a specified time, with a specified number of the product available for sale. The web server cooperates with a separate database computer, separated from the web server computer by a firewall. The database computer is accessible to the web computer server computer to allow selective retrieval of product information, which includes a product description, the quantity of the product to be auctioned, a start price of the product, and an image of the product. The web server computer displays, updated during an auction, the current price of the product, the quantity of the product remaining available for purchase and the measure of the time remaining in the auction. The current price is decreased in a predetermined manner during the auction. Each user is provided with an input instructing the system to purchase the product at a displayed current price, transmitting an identification and required financial authorization for the purchase of the product, which must be confirmed within a predetermined time. In the known system, a certain fall-out rate in the actual purchase confirmation may be assumed, and therefore some overselling allowed. Further, after a purchase is indicate, the user's screen is not updated, obscuring the ultimate lowest selling price from the user. However, if the user maintains a second browser, he can continue to monitor the auction to determine whether the product could have been purchased at a lower price, and if so, fail to confirm the committed purchase and purchase the same goods at a lower price while reserving the goods to avoid risk of loss. Thus, the system is flawed, and may fail to produce an efficient transaction or optimal price.

[0039] An Internet declining price auction system may provide the ability to track the price demand curve, providing valuable marketing information. For example, in trying to determine the response at different prices, companies normally have to conduct market surveys. In contrast, with a declining price auction, substantial information regarding price and demand is immediately known. The relationship between participating bidders and average purchasers can then be applied to provide a conventional price demand curve for the particular product.

[0040] U.S. Pat. No. 5,835,896, Fisher, et al., issued Nov. 10, 1998, expressly incorporated herein by reference in its entirety, provides method and system for processing and transmitting electronic auction information over the Internet, between a central transaction server system and remote bidder terminals. Those bids are recorded by the system and the bidders are updated with the current auction status information. When appropriate, the system closes the auction from further bidding and notifies the winning bidders and losers as to the auction outcome. The transaction server posts information from a database describing a lot available for purchase, receives a plurality of bids, stored in a bid database, in response to the information, and automatically categorizes the bids as successful or unsuccessful. Each bid is validated, and an electronic mail message is sent informing the bidder of the bid status. This system employs HTTP, and thus does not automatically update remote terminal screens, requiring the e-mail notification feature.

[0041] The auction rules may be flexible, for example including Dutch-type auctions, for example by implementing a price markdown feature with scheduled price adjustments, and English-type (progressive) auctions, with price increases corresponding to successively higher bids. In the Dutch type auction, the price markdown feature may be responsive to bidding activity over time, amount of bids received, and number of items bid for. Likewise, in the progressive auction, the award price may be dependent on the quantity desired, and typically implements a lowest successful bid price rule. Bids that are below a preset maximum posted selling price are maintained in reserve by the system. If a certain sales volume is not achieved in a specified period of time, the price is reduced to liquidate demand above the price point, with the new price becoming the posted price. On the other hand, if a certain sales volume is exceeded in a specified period of time, the system may automatically increase the price. These automatic price changes allow the seller to respond quickly to market conditions while keeping the price of the merchandise as high as possible, to the seller's benefit. A “Proxy Bidding” feature allows a bidder to place a bid for the maximum amount they are willing to pay, keeping this value a secret, displaying only the amount necessary to win the item up to the amount of the currently high bids or proxy bids of other bidders. This feature allows bidders to participate in the electronic auction without revealing to the other bidders the extent to which they are willing to increase their bids, while maintaining control of their maximum bid without closely monitoring the bidding. The feature assures proxy bidders the lowest possible price up to a specified maximum without requiring frequent inquiries as to the state of the bidding.

[0042] A “Floating Closing Time” feature may also be implemented whereby the auction for a particular item is automatically closed if no new bids are received within a predetermined time interval, assuming an increasing price auction. Bidders thus have an incentive to place bids expeditiously, rather than waiting until near the anticipated close of the auction.

[0043] U.S. Pat. No.5,905,975, Ausubel, issued May 18, 1999, expressly incorporated herein by reference in its entirety, relates to computer implemented methods and apparatus for auctions. The proposed system provides intelligent systems for the auctioneer and for the user. The auctioneer's system contains information from a user system based on bid information entered by the user. With this information, the auctioneer's system determines whether the auction can be concluded or not and appropriate messages are transmitted. At any point in the auction, bidders are provided the opportunity to submit not only their current bids, but also to enter future bids, or bidding rules which may have the opportunity to become relevant at future times or prices, into the auction system's database. Participants may revise their executory bids, by entering updated bids. Thus, at one extreme, a bidder who wishes to economize on his time may choose to enter his entire set of bidding rules into the computerized system at the start of the auction, effectively treating this as a sealed-bid auction. At the opposite extreme, a bidder who wishes to closely participate in the auction may choose to constantly monitor the auction's progress and to submit all of his bids in real time. See also, U.S. patent application Ser. No.08/582,901 filed Jan. 4, 1996, which provides a method for auctioning multiple, identical objects and close substitutes.

[0044] Secure Networks

[0045] A number of references relate to secure networks, which are an aspect of various embodiments of the present invention. These references are incorporated herein by reference in their entirety, including U.S. Pat. Nos. 5,933,498 (Schneck, et al., Aug. 3, 1999); 5,978,918 (Scholnick, et al., Nov. 2, 1999); 6,005,943 (Cohen, et al., Dec. 21, 1999); 6,009,526 (Choi, Dec. 28, 1999); 6,021,202 (Anderson, et al., Feb. 1, 2000); 6,021,491 (Renaud, Feb. 1, 2000); 6,021,497 (Bouthillier, et al., Feb. 1, 2000); 6,023,762 (Dean, et al., Feb. 8, 2000); 6,029,245 (Scanlan, Feb. 22, 2000); 6,049,875 (Suzuki, et al., Apr. 11, 2000); 6,055,508 (Naor, et al., Apr. 25, 2000); 6,065,119 (Sandford, II, et al., May 16, 2000); 6,073,240 (Kurtzberg, et al., Jun. 6, 2000); 6,075,860 (Ketcham, Jun. 13, 2000); and 6,075,861 (Miller, II, Jun. 13, 2000).

[0046] Cryptographic Technology

[0047] U.S. Pat. No. 5,956,408 (Arnold, Sep. 21, 1999), expressly incorporated herein by reference, relates to an apparatus and method for secure distribution of data. Data, including program and software updates, is encrypted by a public key encryption system using the private key of the data sender. The sender also digitally signs the data. The receiver decrypts the encrypted data, using the public key of the sender, and verifies the digital signature on the transmitted data. The program interacts with basic information stored within the confines of the receiver. As result of the interaction, the software updates are installed within the confines of the user, and the basic information stored within the confines of the user is changed.

[0048] U.S. Pat. Nos. 5,982,891 (Ginter, et al., Nov. 9, 1999); 5,949,876 (Ginter, et al., Sep. 7, 1999); and U.S. Pat. No. 5,892,900 (Ginter, et al., April 6, 1999), expressly incorporated herein by reference, relate to systems and methods for secure transaction management and electronic rights protection. Electronic appliances, such as computers, help to ensure that information is accessed and used only in authorized ways, and maintain the integrity, availability, and/or confidentiality of the information. Such electronic appliances provide a distributed virtual distribution environment (VDE) that may enforce a secure chain of handling and control, for example, to control and/or meter or otherwise monitor use of electronically stored or disseminated information. Such a virtual distribution environment may be used to protect rights of various participants in electronic commerce and other electronic or electronic-facilitated transactions. Distributed and other operating systems, environments and architectures, such as, for example, those using tamper-resistant hardware-based processors, may establish security at each node. These techniques may be used to support an all-electronic information distribution, for example, utilizing the “electronic highway.”

[0049] U.S. Pat. No. 6,009,177 (Sudia, Dec. 28, 1999), expressly incorporated herein by reference, relates to a cryptographic system and method with a key escrow feature that uses a method for verifiably splitting users' private encryption keys into components and for sending those components to trusted agents chosen by the particular users, and provides a system that uses modem public key certificate management, enforced by a chip device that also self-certifies. The methods for key escrow and receiving an escrow certificate are also applied herein to a more generalized case of registering a trusted device with a trusted third party and receiving authorization from that party enabling the device to communicate with other trusted devices. Further preferred embodiments provide for rekeying and upgrading of device firmware using a certificate system, and encryption of stream-oriented data.

[0050] U.S. Pat. No. 6,052,467 (Brands, Apr. 18, 2000), expressly incorporated herein by reference, relates to a system for ensuring that the blinding of secret-key certificates is restricted, even if the issuing protocol is performed in parallel mode. A cryptographic method is disclosed that enables the issuer in a secret-key certificate issuing protocol to issue triples consisting of a secret key, a corresponding public key, and a secret-key certificate of the issuer on the public key, in such a way that receiving parties can blind the public key and the certificate, but cannot blind a predetermined non-trivial predicate of the secret key even when executions of the issuing protocol are performed in parallel.

[0051] U.S. Pat. No. 6,052,780 (Glover, Apr. 18, 2000), expressly incorporated herein by reference, relates to a computer system and process for accessing an encrypted and self-decrypting digital information product while restricting access to decrypted digital information. Some of these problems with digital information protection systems may be overcome by providing a mechanism that allows a content provider to encrypt digital information without requiring either a hardware or platform manufacturer or a content consumer to provide support for the specific form of corresponding decryption. This mechanism can be provided in a manner that allows the digital information to be copied easily for back-up purposes and to be transferred easily for distribution, but which should not permit copying of the digital information in decrypted form. In particular, the encrypted digital information is stored as an executable computer program that includes a decryption program that decrypts the encrypted information to provide the desired digital information, upon successful completion of an authorization procedure by the user. In combination with other mechanisms that track distribution, enforce royalty payments and control access to decryption keys, an improved method is provided for identifying and detecting sources of unauthorized copies. Suitable authorization procedures also enable the digital information to be distributed for a limited number of uses and/or users, thus enabling per-use fees to be charged for the digital information.

[0052] See also, U.S. Pat. Nos. 4,200,770 (Cryptographic apparatus and method); U.S. Pat. No. 4,218,582 (Public key cryptographic apparatus and method); U.S. Pat. No. 4,264,782 (Method and apparatus for transaction and identity verification); U.S. Pat. No. 4,306,111 (Simple and effective public-key cryptosystem); U.S. Pat. No. 4,309,569 (Method of providing digital signatures); U.S. Pat. No. 4,326,098 (High security system for electronic signature verification); U.S. Pat. No. 4,351,982 (RSA Public-key data encryption system having large random prime number generating microprocessor or the like); U.S. Pat. No. 4,365,110 (Multiple-destinational cryptosystem for broadcast networks); U.S. Pat. No. 4,386,233 (Crytographic key notarization methods and apparatus); U.S. Pat. No. 4,393,269 (Method and apparatus incorporating a one-way sequence for transaction and identity verification); U.S. Pat. No. 4,399,323 (Fast real-time public key cryptography); U.S. Pat. No. 4,405,829 (Cryptographic communications system and method); U.S. Pat. No. 4,438,824 (Apparatus and method for cryptographic identity verification); U.S. Pat. No. 4,453,074 (Protection system for intelligent cards); U.S. Pat. No. 4,458,109 (Method and apparatus providing registered mail features in an electronic communication system); U.S. Pat. No. 4,471,164 (Stream cipher operation using public key cryptosystem); U.S. Pat. No. 4,514,592 (Cryptosystem); U.S. Pat. No. 4,528,588 (Method and apparatus for marking the information content of an information carrying signal); U.S. Pat. No. 4,529,870 (Cryptographic identification, financial transaction, and credential device); U.S. Pat. No. 4,558,176 (Computer systems to inhibit unauthorized copying, unauthorized usage, and automated cracking of protected software); U.S. Pat. No. 4,567,600 (Method and apparatus for maintaining the privacy of digital messages conveyed by public transmission); U.S. Pat. No. 4,575,621 (Portable electronic transaction device and system therefor); U.S. Pat. No. 4,578,531 (Encryption system key distribution method and apparatus); U.S. Pat. No. 4,590,470 (User authentication system employing encryption functions); U.S. Pat. No. 4,595,950 (Method and apparatus for marking the information content of an information carrying signal); U.S. Pat. No. 4,625,076 (Signed document transmission system); U.S. Pat. No. 4,633,036 (Method and apparatus for use in public-key data encryption system); U.S. Pat. No. 5,991,406 (System and method for data recovery); U.S. Pat. No. 6,026,379 (System, method and article of manufacture for managing transactions in a high availability system); U.S. Pat. No. 6,026,490 (Configurable cryptographic processing engine and method); U.S. Pat. No. 6,028,932 (Copy prevention method and apparatus for digital video system); U.S. Pat. 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No. 6,038,666 (Remote identity verification technique using a personal identification device); U.S. Pat. No. 6,041,122 (Method and apparatus for hiding cryptographic keys utilizing autocorrelation timing encoding and computation); U.S. Pat. No. 6,041,123 (Centralized secure communications system); U.S. Pat. No. 6,041,357 (Common session token system and protocol); U.S. Pat. No. 6,041,408 (Key distribution method and system in secure broadcast communication); U.S. Pat. No. 6,041,410 (Personal identification fob); U.S. Pat. No. 6,044,131 (Secure digital x-ray image authentication method); U.S. Pat. No. 6,044,155 (Method and system for securely archiving core data secrets); U.S. Pat. No. 6,044,157 (Microprocessor suitable for reproducing AV data while protecting the AV data from illegal copy and image information processing system using the microprocessor); U.S. Pat. No. 6,044,205 (Communications system for transferring information between memories according to processes transferred with the information); U.S. Pat. No. 6,044,349 (Secure and convenient information storage and retrieval method and apparatus); U.S. Pat. No. 6,044,350 (Certificate meter with selectable indemnification provisions); U.S. Pat. No. 6,044,388 (Pseudorandom number generator); U.S. Pat. No. 6,044,462 (Method and apparatus for managing key revocation); U.S. Pat. No. 6,044,463 (Method and system for message delivery utilizing zero knowledge interactive proof protocol); U.S. Pat. No. 6,044,464 (Method of protecting broadcast data by fingerprinting a common decryption function); U.S. Pat. No. 6,044,466 (Flexible and dynamic derivation of permissions); U.S. Pat. No. 6,044,468 (Secure transmission using an ordinarily insecure network communication protocol such as SNMP); U.S. Pat. No. 6,047,051 (Implementation of charging in a telecommunications system); U.S. Pat. No. 6,047,066 (Communication method and device); U.S. Pat. No. 6,047,067 (Electronic-monetary system); U.S. Pat. No. 6,047,072 (Method for secure key distribution over a nonsecure communications network); U.S. Pat. No. 6,047,242 (Computer system for protecting software and a method for protecting software); U.S. Pat. No. 6,047,268 (Method and apparatus for billing for transactions conducted over the internet); U.S. Pat. No. 6,047,269 (Self-contained payment system with circulating digital vouchers); U.S. Pat. No. 6,047,374 (Method and apparatus for embedding authentication information within digital data); U.S. Pat. No. 6,047,887 (System and method for connecting money modules); U.S. Pat. No. 6,049,610 (Method and apparatus for digital signature authentication); U.S. Pat. No. 6,049,612 (File encryption method and system); U.S. Pat. No. 6,049,613 (Method and apparatus for encrypting, decrypting, and providing privacy for data values); U.S. Pat. No. 6,049,671 (Method for identifying and obtaining computer software from a network computer); U.S. Pat. No. 6,049,785 (Open network payment system for providing for authentication of payment orders based on a confirmation electronic mail message); U.S. Pat. No. 6,049,786 (Electronic bill presentment and payment system which deters cheating by employing hashes and digital signatures); U.S. Pat. No. 6,049,787 (Electronic business transaction system with notarization database and means for conducting a notarization procedure); U.S. Pat. No. 6,049,838 (Persistent distributed capabilities); U.S. Pat. No. 6,049,872 (Method for authenticating a channel in large-scale distributed systems); U.S. Pat. No. 6,049,874 (System and method for backing up computer files over a wide area computer network); U.S. Pat. No. 6,052,466 (Encryption of data packets using a sequence of private keys generated from a public key exchange); U.S. Pat. No. 6,052,467 (System for ensuring that the blinding of secret-key certificates is restricted, even if the issuing protocol is performed in parallel mode); U.S. Pat. No. 6,052,469 (Interoperable cryptographic key recovery system with verification by comparison); U.S. Pat. No. 6,055,314 (System and method for secure purchase and delivery of video content programs); U.S. Pat. No. 6,055,321 (System and method for hiding and extracting message data in multimedia data); U.S. Pat. No. 6,055,508 (Method for secure accounting and auditing on a communications network); U.S. Pat. No. 6,055,512 (Networked personal customized information and facility services); U.S. Pat. No. 6,055,636 (Method and apparatus for centralizing processing of key and certificate life cycle management); U.S. Pat. No. 6,055,639 (Synchronous message control system in a Kerberos domain); U.S. Pat. No. 6,056,199 (Method and apparatus for storing and reading data); U.S. Pat. No. 6,057,872 (Digital coupons for pay televisions); U.S. Pat. No. 6,058,187 (Secure telecommunications data transmission); U.S. Pat. No. 6,058,188 (Method and apparatus for interoperable validation of key recovery information in a cryptographic system); U.S. Pat. No. 6,058,189 (Method and system for performing secure electronic monetary transactions); U.S. Pat. No. 6,058,193 (System and method of verifying cryptographic postage evidencing using a fixed key set); U.S. Pat. No. 6,058,381 (Many-to-many payments system for network content materials); U.S. Pat. No. 6,058,383 (Computationally efficient method for trusted and dynamic digital objects dissemination); U.S. Pat. No. 6,061,448 (Method and system for dynamic server document encryption); U.S. Pat. No. 6,061,454 (System, method, and computer program for communicating a key recovery block to enable third party monitoring without modification to the intended receiver); U.S. Pat. No. 6,061,692 (System and method for administering a meta database as an integral component of an information server); U.S. Pat. No. 6,061,789 (Secure anonymous information exchange in a network); U.S. Pat. No. 6,061,790 (Network computer system with remote user data encipher methodology); U.S. Pat. No. 6,061,791 (Initial secret key establishment including facilities for verification of identity); U.S. Pat. No. 6,061,792 (System and method for fair exchange of time-independent information goods over a network); U.S. Pat. No. 6,061,794 (System and method for performing secure device communications in a peer-to-peer bus architecture); U.S. Pat. No. 6,061,796 (Multi-access virtual private network); U.S. Pat. No. 6,061,799 (Removable media for password based authentication in a distributed system); U.S. Pat. No. 6,064,723 (Network-based multimedia communications and directory system and method of operation); U.S. Pat. No. 6,064,738 (Method for encrypting and decrypting data using chaotic maps); U.S. Pat. No. 6,064,740 (Method and apparatus for masking modulo exponentiation calculations in an integrated circuit); U.S. Pat. No. 6,064,741 (Method for the computer-aided exchange of cryptographic keys between a user computer unit U and a network computer unit N); U.S. Pat. No. 6,064,764 (Fragile watermarks for detecting tampering in images); U.S. Pat. No. 6,064,878 (Method for separately permissioned communication); U.S. Pat. No. 6,065,008 (System and method for secure font subset distribution); U.S. Pat. No. 6,067,620 (Stand alone security device for computer networks); U.S. Pat. No. 6,069,647 (Conditional access and content security method); U.S. Pat. No. 6,069,952 (Data copyright management system); U.S. Pat. No. 6,069,954 (Cryptographic data integrity with serial bit processing and pseudo-random generators); U.S. Pat. No. 6,069,955 (System for protection of goods against counterfeiting); U.S. Pat. No. 6,069,969 (Apparatus and method for electronically acquiring fingerprint images); U.S. Pat. No. 6,069,970 (Fingerprint sensor and token reader and associated methods); U.S. Pat. No. 6,070,239 (System and method for executing verifiable programs with facility for using non-verifiable programs from trusted sources); U.S. Pat. No. 6,072,870 (System, method and article of manufacture for a gateway payment architecture utilizing a multichannel, extensible, flexible architecture); U.S. Pat. No. 6,072,874 (Signing method and apparatus using the same); U.S. Pat. No. 6,072,876 (Method and system for depositing private key used in RSA cryptosystem); U.S. Pat. No. 6,073,125 (Token key distribution system controlled acceptance mail payment and evidencing system); U.S. Pat. No. 6,073,160 (Document communications controller); U.S. Pat. No. 6,073,172 (Initializing and reconfiguring a secure network interface); U.S. Pat. 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No. 6,076,167 (Method and system for improving security in network applications); U.S. Pat. No. 6,078,663 (Communication apparatus and a communication system); U.S. Pat. No. 6,078,665 (Electronic encryption device and method); U.S. Pat. No. 6,078,667 (Generating unique and unpredictable values); U.S. Pat. No. 6,078,909 (Method and apparatus for licensing computer programs using a DSA signature); U.S. Pat. No. 6,079,018 (System and method for generating unique secure values for digitally signing documents); U.S. Pat. No. 6,079,047 (Unwrapping system and method for multiple files of a container); U.S. Pat. No. 6,081,597 (Public key cryptosystem method and apparatus); U.S. Pat. No. 6,081,598 (Cryptographic system and method with fast decryption); U.S. Pat. No. 6,081,610 (System and method for verifying signatures on documents); U.S. Pat. No. 6,081,790 (System and method for secure presentment and payment over open networks); U.S. Pat. No. 6,081,893 (System for supporting secured log-in of multiple users into a plurality of computers using combined presentation of memorized password and transportable passport record), U.S. Pat. No. 6,192,473 (System and method for mutual authentication and secure communications between a postage security device and a meter server), each of which is expressly incorporated herein by reference.

[0053] See, also, U.S. Pat. Nos. 6,028,937 (Tatebayashi et al.), U.S. Pat. No. 6,026,167 (Aziz), U.S. Pat. No. 6,009,171 (Ciacelli et al.) (Content Scrambling System, or “CSS”), U.S. Pat. No. 5,991,399 (Graunke et al.), U.S. Pat. No. 5,948,136 (Smyers) (IEEE 1394-1995), and U.S. Pat. No. 5,915,018 (Aucsmith), expressly incorporated herein by reference, and Jim Wright and Jeff Robillard (Philsar Semiconductor), “Adding Security to Portable Designs”, Portable Design, March 2000, pp. 16-20.

[0054] See also, Stefik, U.S. Pat. Nos. 5,715,403 (System for controlling the distribution and use of digital works having attached usage rights where the usage rights are defined by a usage rights grammar); U.S. Pat. No. 5,638,443 (System for controlling the distribution and use of composite digital works); U.S. Pat. No. 5,634,012 (System for controlling the distribution and use of digital works having a fee reporting mechanism); and U.S. Pat. No. 5,629,980 (System for controlling the distribution and use of digital works), expressly incorporated herein by reference.

[0055] Computer Security and Devices

[0056] A number of references relate to computer system security, which is a part of various embodiment of the invention. The following references relevant to this issue are incorporated herein by reference: U.S. Pat. No. 5,881,225 (Worth, Mar. 9, 1999); U.S. Pat. No. 5,937,068 (Audebert, Aug. 10, 1999); U.S. Pat. No. 5,949,882 (Angelo, Sep. 7, 1999); U.S. Pat. No. 5,953,419 (Lohstroh, et al., Sep. 14, 1999); U.S. Pat. No. 5,956,400 (Chaum, et al., Sep. 21, 1999); U.S. Pat. No. 5,958,050 (Griffin, et al., Sep. 28, 1999); U.S. Pat. No. 5,978,475 (Schneier, et al., Nov. 2, 1999); U.S. Pat. No. 5,991,878 (McDonough, et al., Nov. 23, 1999); U.S. Pat. No. 6,070,239 (McManis, May 30, 2000); and U.S. Pat. No. 6,079,021 (Abadi, et al., Jun. 20, 2000).

[0057] A number of references relate to computer security devices, which is a part of various embodiment of the invention. The following references relevant to this issue are incorporated herein by reference: U.S. Pat. Nos. 5,982,520 (Weiser, et al., Nov. 9, 1999); U.S. Pat. No. 5,991,519 (Benhammou, et al., Nov. 23, 1999); U.S. Pat. No. 5,999,629 (Heer, et al., Dec. 7, 1999); U.S. Pat. No. 6,034,618 (Tatebayashi, et al., Mar. 7, 2000); U.S. Pat. No. 6,041,412 (Timson, et al., Mar. 21, 2000); U.S. Pat. No. 6,061,451 (Muratani, et al., May 9, 2000); and U.S. Pat. No. 6,069,647 (Sullivan, et al., May 30, 2000).

[0058] Virtual Private Network

[0059] A number of references relate to virtual private networks, which is a part of various embodiment of the invention. The following references relevant to this issue are incorporated herein by reference: U.S. Pat. No. 6,079,020 (Liu, Jun. 20, 2000); U.S. Pat. No. 6,081,900 (Secure intranet access); U.S. Pat. No. 6,081,533 (Method and apparatus for an application interface module in a subscriber terminal unit); U.S. Pat. No. 6,079,020 (Method and apparatus for managing a virtual private network); U.S. Pat. No. 6,078,946 (System and method for management of connection oriented networks); U.S. Pat. No. 6,078,586 (ATM virtual private networks); U.S. Pat. No. 6,075,854 (Fully flexible routing service for an advanced intelligent network); U.S. Pat. No. 6,075,852 (Telecommunications system and method for processing call-independent signalling transactions); U.S. Pat. No. 6,073,172 (Initializing and reconfiguring a secure network interface); U.S. Pat. No. 6,061,796 (Multi-access virtual private network); U.S. Pat. No. 6,061,729 (Method and system for communicating service information in an advanced intelligent network); U.S. Pat. No. 6,058,303 (System and method for subscriber activity supervision); U.S. Pat. No. 6,055,575 (Virtual private network system and method); U.S. Pat. No. 6,052,788 (Firewall providing enhanced network security and user transparency); U.S. Pat. No. 6,047,325 (Network device for supporting construction of virtual local area networks on arbitrary local and wide area computer networks); U.S. Pat. No. 6,032,118 (Virtual private network service provider for asynchronous transfer mode network); U.S. Pat. No. 6,029,067 (Virtual private network for mobile subscribers); U.S. Pat. No. 6,016,318 (Virtual private network system over public mobile data network and virtual LAN); U.S. Pat. No. 6,009,430 (Method and system for provisioning databases in an advanced intelligent network); U.S. Pat. No. 6,005,859 (Proxy VAT-PSTN origination); U.S. Pat. No. 6,002,767 (System, method and article of manufacture for a modular gateway server architecture); U.S. Pat. No. 6,002,756 (Method and system for implementing intelligent telecommunication services utilizing self-sustaining, fault-tolerant object oriented architecture), each of which is expressly incorporated herein by reference.

[0060] See also, U.S. Pat. Nos. 6,081,900 (Secure intranet access); U.S. Pat. No. 6,081,750 (Ergonomic man-machine interface incorporating adaptive pattern recognition based control system); U.S. Pat. No. 6,081,199 (Locking device for systems access to which is time-restricted); U.S. Pat. No. 6,079,621 (Secure card for E-commerce and identification); U.S. Pat. No. 6,078,265 (Fingerprint identification security system); U.S. Pat. No. 6,076,167 (Method and system for improving security in network applications); U.S. Pat. No. 6,075,455 (Biometric time and attendance system with epidermal topographical updating capability); U.S. Pat. No. 6,072,894 (Biometric face recognition for applicant screening); U.S. Pat. No. 6,070,141 (System and method of assessing the quality of an identification transaction using an identification quality score); U.S. Pat. No. 6,068,184 (Security card and system for use thereof); U.S. Pat. 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[0061] E-Commerce Systems

[0062] U.S. Pat. No. 5,946,669 (Polk, Aug. 31, 1999), expressly incorporated herein by reference, relates to a method and apparatus for payment processing using debit-based electronic funds transfer and disbursement processing using addendum-based electronic data interchange. This disclosure describes a payment and disbursement system, wherein an initiator authorizes a payment and disbursement to a collector and the collector processes the payment and disbursement through an accumulator agency. The accumulator agency processes the payment as a debit-based transaction and processes the disbursement as an addendum-based transaction. The processing of a debit-based transaction generally occurs by electronic funds transfer (EFT) or by financial electronic data interchange (FEDI). The processing of an addendum-based transaction generally occurs by electronic data interchange (EDI).

[0063] U.S. Pat. No. 6,005,939 (Fortenberry, et al., Dec. 21, 1999), expressly incorporated herein by reference, relates to a method and apparatus for storing an Internet user's identity and access rights to World Wide Web resources. A method and apparatus for obtaining user information to conduct secure transactions on the Internet without having to re-enter the information multiple times is described. The method and apparatus can also provide a technique by which secured access to the data can be achieved over the Internet. A passport containing user-defined information at various security levels is stored in a secure server apparatus, or passport agent, connected to computer network. A user process instructs the passport agent to release all or portions of the passport to a recipient node and forwards a key to the recipient node to unlock the passport information.

[0064] U.S. Pat. No. 6,016,484 (Williams, et al., Jan. 18, 2000), expressly incorporated herein by reference, relates to a system, method and apparatus for network electronic payment instrument and certification of payment and credit collection utilizing a payment. An electronic monetary system provides for transactions utilizing an electronic-monetary system that emulates a wallet or a purse that is customarily used for keeping money, credit cards and other forms of payment organized. Access to the instruments in the wallet or purse is restricted by a password to avoid unauthorized payments. A certificate form must be completed in order to obtain an instrument. The certificate form obtains the information necessary for creating a certificate granting authority to utilize an instrument, a payment holder and a complete electronic wallet. Electronic approval results in the generation of an electronic transaction to complete the order. If a user selects a particular certificate, a particular payment instrument holder will be generated based on the selected certificate. In addition, the issuing agent for the certificate defines a default bitmap for the instrument associated with a particular certificate, and the default bitmap will be displayed when the certificate definition is completed. Finally, the number associated with a particular certificate will be utilized to determine if a particular party can issue a certificate.

[0065] U.S. Pat. No. 6,029,150 (Kravitz, Feb. 22, 2000), expressly incorporated herein by reference, relates to a system and method of payment in an electronic payment system wherein a plurality of customers have accounts with an agent. A customer obtains an authenticated quote from a specific merchant, the quote including a specification of goods and a payment amount for those goods. The customer sends to the agent a single communication including a request for payment of the payment amount to the specific merchant and a unique identification of the customer. The agent issues to the customer an authenticated payment advice based only on the single communication and secret shared between the customer and the agent and status information, which the agent knows about the merchant, and/or the customer. The customer forwards a portion of the payment advice to the specific merchant. The specific merchant provides the goods to the customer in response to receiving the portion of the payment advice.

[0066] U.S. Pat. No. 6,047,269 (Biffar, Apr. 4, 2000), expressly incorporated herein by reference, relates to a self-contained payment system with creating and facilitating transfer of circulating digital vouchers representing value. A digital voucher has an identifying element and a dynamic log. The identifying element includes information such as the transferable value, a serial number and a digital signature. The dynamic log records the movement of the voucher through the system and accordingly grows over time. This allows the system operator to not only reconcile the vouchers before redeeming them, but also to recreate the history of movement of a voucher should an irregularity like a duplicate voucher be detected. These vouchers are used within a self-contained system including a large number of remote devices that are linked to a central system. The central system can e linked to an external system. The external system, as well as the remote devices, is connected to the central system by any one or a combination of networks. The networks must be able to transport digital information, for example the Internet, cellular networks, telecommunication networks, cable networks or proprietary networks. Vouchers can also be transferred from one remote device to another remote device. These remote devices can communicate through a number of methods with each other. For example, for a non-face-to-face transaction the Internet is a choice, for a face-to-face or close proximity transactions tone signals or light signals are likely methods. In addition, at the time of a transaction a digital receipt can be created which will facilitate a fast replacement of vouchers stored in a lost remote device.

[0067] Micropayments

[0068] U.S. Pat. No. 5,999,919 (Jarecki, et al., Dec. 7, 1999), expressly incorporated herein by reference, relates to an efficient micropayment system. Existing software proposals for electronic payments can be divided into “on-line” schemes which require participation of a trusted party (the bank) in every transaction and are secure against overspending, and “off-line” schemes which do not require a third party and guarantee only that overspending is detected when vendors submit their transaction records to the bank (usually at the end of the day). A new “hybrid” scheme is proposed which combines the advantages of both “on-line” and “off-line” electronic payment schemes. It allows for control of overspending at a cost of only a modest increase in communication compared to the off-line schemes. The protocol is based on probabilistic polling. During each transaction, with some small probability, the vendor forwards information about this transaction to the bank. This enables the bank to maintain an accurate approximation of a customer's spending. The frequency of polling messages is related to the monetary value of transactions and the amount of overspending the bank is willing to risk. For transactions of high monetary value, the cost of polling approaches that of the on-line schemes, but for micropayments, the cost of polling is a small increase over the traffic incurred by the off-line schemes.

[0069] Micropayments are often preferred where the amount of the transaction does not justify the costs of complete financial security. In the micropayment scheme, typically a direct communication between creditor and debtor is not required; rather, the transaction produces a result which eventually results in an economic transfer, but which may remain outstanding subsequent to transfer of the underlying goods or services. The theory underlying this micropayment scheme is that the monetary units are small enough such that risks of failure in transaction closure is relatively insignificant for both parties, but that a user gets few chances to default before credit is withdrawn. On the other hand, the transaction costs of a non-real time transactions of small monetary units are substantially less than those of secure, unlimited or potentially high value, real time verified transactions, allowing and facilitating such types of commerce. Thus, the rights management system may employ applets local to the client system, which communicate with other applets and/or the server and/or a vendor/rights-holder to validate a transaction, at low transactional costs.

[0070] The following U.S. Patents, expressly incorporated herein by reference, define aspects of micropayment, digital certificate, and on-line payment systems: U.S. Pat. No. 5,930,777 (Barber, Jul. 27, 1999, Method of charging for pay-per-access information over a network); U.S. Pat. No. 5,857,023 (Jan. 5, 1999, Demers et al., Space efficient method of redeeming electronic payments); U.S. Pat. No. 5,815,657 (Sep. 29, 1998, Williams, System, method and article of manufacture for network electronic authorization utilizing an authorization instrument); U.S. Pat. No. 5,793,868 (Aug. 11, 1998, Micali, Certificate revocation system), U.S. Pat. No. 5,717,757 (Feb. 10, 1998, Micali, Certificate issue lists); U.S. Pat. No. 5,666,416 (Sep. 9, 1997, Micali, Certificate revocation system); U.S. Pat. No. 5,677,955 (Doggett et al., Electronic funds transfer instruments); U.S. Pat. No. 5,839,119 (Nov. 17, 1998, Krsul; et al., Method of electronic payments that prevents double-spending); U.S. Pat. No. 5,915,093 (Berlin et al.); 5,937,394 (Wong, et al.); U.S. Pat. No. 5,933,498 (Schneck et al.); U.S. Pat. No. 5,903,880 (Biffar); U.S. Pat. No. 5,903,651 (Kocher); 5,884,277 (Khosla); U.S. Pat. No. 5,960,083 (Sep. 28, 1999, Micali, Certificate revocation system); U.S. Pat. No. 5,963,924 (Oct. 5, 1999, Williams et al., System, method and article of manufacture for the use of payment instrument holders and payment instruments in network electronic commerce); U.S. Pat. No. 5,996,076 (Rowney et al., System, method and article of manufacture for secure digital certification of electronic commerce); U.S. Pat. No. 6,016,484 (Jan 18, 2000, Williams et al., System, method and article of manufacture for network electronic payment instrument and certification of payment and credit collection utilizing a payment); U.S. Pat. No. 6,018,724 (Arent); U.S. Pat. No. 6,021,202 (Anderson et al., Method and system for processing electronic documents); U.S. Pat. No. 6,035,402 (Vaeth et al.); U.S. Pat. No. 6,049,786 (Smorodinsky); U.S. Pat. No. 6,049,787 (Takahashi, et al.); U.S. Pat. No. 6,058,381 (Nelson, Many-to-many payments system for network content materials); U.S. Pat. No. 6,061,448 (Smith, et al.); U.S. Pat. No. 5,987,132 (Nov. 16, 1999, Rowney, System, method and article of manufacture for conditionally accepting a payment method utilizing an extensible, flexible architecture); U.S. Pat. No. 6,057,872 (Candelore); and U.S. Pat. No. 6,061,665 (May 9, 2000, Bahreman, System, method and article of manufacture for dynamic negotiation of a network payment framework). See also, Rivest and Shamir, “PayWord and MicroMint: Two Simple Micropayment Schemes” (May 7, 1996); Micro PAYMENT transfer Protocol (MPTP) Version 0.1 (22 Nov. 1995) et seq., http://www.w3.org/pub/WWW/TR/WD-mptp; Common Markup for web Micropayment Systems, http://www.w3.org/TR/WD-Micropayment-Markup (09Jun. 1999); “Distributing Intellectual Property: a Model of Microtransaction Based Upon Metadata and Digital Signatures”, Olivia, Maurizio, http://olivia.modlang.denison.edu/˜olivia/RFC/09/, all of which are expressly incorporated herein by reference.

[0071] See, also: U.S. Pat. No. 4,977,595 (Dec. 11, 1990, Method and apparatus for implementing electronic cash); U.S. Pat. No. 5,224,162 (Jun. 29, 1993, Electronic cash system); U.S. Pat. No. 5,237,159 (Aug. 17, 1993, Electronic check presentment system); U.S. Pat. No. 5,392,353 (February 1995, Morales, TV Answer, Inc. Interactive satellite broadcast network); U.S. Pat. No. 5,511,121 (Apr. 23, 1996, Efficient electronic money); U.S. Pat. No. 5,621,201 (April 1997, Langhans et al., Visa International Automated purchasing control system); U.S. Pat. No. 5,623,547 (Apr. 22, 1997, Value transfer system); U.S. Pat. No. 5,679,940 (October 1997, Templeton et al., TeleCheck International, Inc. Transaction system with on/off line risk assessment); U.S. Pat. No. 5,696,908 (December 1997, Muehlberger et al., Southeast Phonecard, Inc. Telephone debit card dispenser and method); U.S. Pat. No. 5,754,939 (May 1998, Herz et al., System for generation of user profiles for a system for customized electronic identification of desirable objects); U.S. Pat. No. 5,768,385 (Jun. 16, 1998, Untraceable electronic cash); U.S. Pat. No. 5,799,087 (Aug. 25, 1998, Electronic-monetary system); U.S. Pat. No 5,812,668 (Sep.22, 1998, System, method and article of manufacture for verifying the operation of a remote transaction clearance system utilizing a multichannel, extensible, flexible architecture); U.S. Pat. No. 5,828,840 (Oct. 27, 1998, Server for starting client application on client if client is network terminal and initiating client application on server if client is non network terminal); U.S. Pat. No. 5,832,089 (Nov. 3, 1998, Off-line compatible electronic cash method and system); U.S. Pat. No. 5,850,446 (Dec. 15, 1998, System, method and article of manufacture for virtual point of sale processing utilizing an extensible, flexible architecture); U.S. Pat. No. 5,889,862 (Mar. 30, 1999, Method and apparatus for implementing traceable electronic cash); U.S. Pat. No. 5,889,863 (Mar. 30, 1999, System, method and article of manufacture for remote virtual point of sale processing utilizing a multichannel, extensible, flexible architecture); U.S. Pat. No. 5,898,154 (Apr. 27, 1999, System and method for updating security information in a time-based electronic monetary system); U.S. Pat. No. 5,901,229 (May 4, 1999, Electronic cash implementing method using a trustee); U.S. Pat. No. 5,920,629 (Jul. 6, 1999, Electronic-monetary system); U.S. Pat. No. 5,926,548 (Jul. 20, 1999, Method and apparatus for implementing hierarchical electronic cash); U.S. Pat. No. 5,943,424 (Aug. 24, 1999, System, method and article of manufacture for processing a plurality of transactions from a single initiation point on a multichannel, extensible, flexible architecture); U.S. Pat. No. 5,949,045 (Sep. 7, 1999, Micro-dynamic simulation of electronic cash transactions); U.S. Pat. No. 5,952,638 (Sep. 14, 1999, Space efficient method of electronic payments); U.S. Pat. No. 5,963,648 (Oct. 5, 1999, Electronic-monetary system); U.S. Pat. No. 5,978,840 (System, method and article of manufacture for a payment gateway system architecture for processing encrypted payment transactions utilizing a multichannel, extensible, flexible architecture); U.S. Pat. No. 5,983,208 (Nov. 9, 1999, System, method and article of manufacture for handling transaction results in a gateway payment architecture utilizing a multichannel, extensible, flexible architecture); U.S. Pat. No. 5,987,140 (Nov. 16, 1999, System, method and article of manufacture for secure network electronic payment and credit collection); U.S. Pat. No. 6,002,767 (Dec. 14, 1999, System, method and article of manufacture for a modular gateway server architecture); U.S. Pat. No. 6,003,765 (Dec. 21, 1999, Electronic cash implementing method with a surveillance institution, and user apparatus and surveillance institution apparatus for implementing the same); U.S. Pat. No. 6,021,399 (Feb. 1, 2000, Space efficient method of verifying electronic payments); U.S. Pat. No. 6,026,379 (Feb. 15, 2000, System, method and article of manufacture for managing transactions in a high availability system); U.S. Pat. No. 6,029,150 (Feb. 22, 2000, Payment and transactions in electronic commerce system); U.S. Pat. No. 6,029,151 (Feb. 22, 2000, Method and system for performing electronic money transactions); U.S. Pat. No. 6,047,067 (Apr. 4, 2000, Electronic-monetary system); U.S. Pat. No. 6,047,887 (Apr.11, 2000, System and method for connecting money modules); U.S. Pat. No. 6,055,508 (Apr. 25, 2000, Method for secure accounting and auditing on a communications network); U.S. Pat. No. 6,065,675 (May 23, 2000, Processing system and method for a heterogeneous electronic cash environment); U.S. Pat. No. 6,072,870 (Jun. 6, 2000, System, method and article of manufacture for a gateway payment architecture utilizing a multichannel, extensible, flexible architecture), each of which is expressly incorporated herein by reference.

[0072] Neural Networks

[0073] The resources relating to Neural Networks, listed in the Neural Networks References Appendix, each of which is expressly incorporated herein by reference, provides a sound basis for understanding the field of neural networks (and the subset called artificial neural networks, which distinguish biological systems) and how these might be used to solve problems. A review of these references will provide a state of knowledge appropriate for an understanding of aspects of the invention which rely on Neural Networks, and to avoid a prolix discussion of no benefit to those already possessing an appropriate state of knowledge.

[0074] Telematics

[0075] The resources relating to telematics listed in the Telematics Appendix, each of which is expressly incorporated herein by reference, provides a background in the theory and practice of telematics, as well as some of the underlying technologies. A review of these references is therefore useful in inderstanding practical issues and the context of functions and technologies which may be used in conjunction with the advances set forth herein.

[0076] Game Theory

[0077] The following resources listed in the Game Theory References Appendix, relating to Game Theory, each of which is expressly incorporated herein by reference, provides a basis for understanding Game Theory and its implications for the design, control, and analysis of systems and networks. A review of these references will assure a background in this field for an understanding of aspects of the invention which relate to game Theory.

[0078] Use of Game Theory to Control Ad Hoc Networks

[0079] The resources relating to ad hoc networks and game theory listed in the Game Theory and Ad Hoc Netowrks References Appendix, each of which is expressly incorporated herein by reference, provides a sound basis for understanding the implications of game theory for the design, control and analysis of communications networks, and in particular, ad hoc networks. A review of these references will assure a background in this field for an understanding of aspects of the invention which rely on these topics.

[0080] Other Patents by Inventor Hereof

[0081] The following patents are expressly incorporated herein by reference: U.S. Patent Nos. 6,640,145, 6,418,424, 6,400,996, 6,081,750, 5,920,477, 5,903,454, 5,901,246, 5,875,108, 5,867,386, 5,774,357, 6,429,812, and 6,252,544.

[0082] The following references are provided as enhancements to the present disclosure and to provide a service to the art in consolidating these citations in a single location. A review of all of these references is not believed necessary for an understanding of the invention, but given the range of arts encompassed, may be supplemental and provide an understanding for one who is not expert in all areas encompassed by the present disclosure.

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[0180] An approach to dynamic reconfiguration of.—Almeida, Wegdam. (2001) www.cs.utwente.nl/˜alme/cvitae/sbrc2001 -final-footnote.pdf www.ub.utwente.nl/webdocs/ctit/1/0000004f.pdf

[0181] A GSM/GPS Receiver With a Bandpass Sigma-Delta Analog.—Müller, Boehm, Hentschel (1999) www.ifn.et.tu-dresden.de/MNS/veroeffentlichungen/1999/Mueller_T_EUW_—99.pdf

[0182] An Intelligent Educational Metadata Repository—Bassiliades, Kokkoras. (2002) www.csd.auth.gr/%7Elpis/publications/crc-chapter1.pdf

[0183] Messor: Load-Balancing through a Swarm of Autonomous Agents—Montresor, Meling, Babaoglu (2002) www.cs.unibo.it/babaoglu/papers/ap2p02.pdf

[0184] Exact trade-off between approximation accuracy and.—Tikk, Baranyi www.mft.hu/publications/baranyi/baranyi2.pdf

[0185] On the Queue Tail Asymptotics for General Multifractal Traffic—Molnar, Dang, Maricza hsnlab.ttt.bme.hu/˜molnar/files/ifipnw02.pdf

[0186] Feature Ranking Based On Interclass Separability For Fuzzy.—Tikk, Gedeon (2000) www.mft.hu/publications/tikk/tikk8.pdf

[0187] Public Key Certificate Revocation Schemes—Arnes (2000) www.pvv.ntnu.no/˜andrearn/certrev/thesis/CertRevThesis_—29Feb2000.ps.gz

[0188] Competitive market-based allocation of consumer attention.—Bohte, Gerding. (2001) www.cwi.nl/ftp/CWIreports/SEN/SEN-R0131.ps.Z

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[0190] Stability of interpolative fuzzy KH controllers—Tikk, Joó. (2002) www.mft.hu/publications/tikk/tikk4.pdf

[0191] Comprehensive analysis of a new fuzzy rule interpolation method—Tikk, Baranyi (2000) www.mft.hu/publications/tikk/tikk2.pdf

[0192] Design and Use of Clinical Ontologies:—Curricular Goals For www-smi.stanford.edu/pubs/SMI_Reports/SMI-1999-0767.pdf

[0193] Toward Standardization of Electronic Guideline.—Elkin, Peleg, Lacson, . (2000) www-smi.stanford.edu/pubs/SMI_Reports/SMI-2001-0865.pdf

[0194] Extracting Information for Automatic Indexing of Multimedia Material—Saggion. (2002) parlevink.cs.utwente.nl/projects/mumis/documents/mumis-lrec2002.pdf

[0195] Investigation of a new alpha-cut based fuzzy.—Baranyi, Tikk, Yam. www.mft.hu/publications/tikk/tikk11.pdf

[0196] The Evolution of Jini″ Technology—In Telematics By wwws.sun.com/software/jini/whitepapers/PsiNapticTelematics.pdf

[0197] Desktop Synchronous Distance Learning Application—Enhanced With Efficient ru6.cti.gr/Publications/645.pdf; ru6.cti.gr/Publications/904.pdf

[0198] Adaptive compression of DICOM-image data—Hludov, Engel, Meinel www.informatik.uni-trier.de/˜meinel/papers/tes_—2.ps

[0199] Telematic Tools to Support Group Projects in Higher Education—Jan Van Der www.ub.utwente.nl/webdocs/ctit/1/00000004.pdf

[0200] A Receiver-initiated WDM Multicast Tree Construction Protocol.—Ip Dense Mode www.ub.utwente.nl/webdocs/ctit/ 1/00000032.pdf

[0201] AUTOLINK—A Tool for the Automatic and.—Schmitt, Koch. (1997) 141.83.21.121 /publications/ALASA/SchmKochGraHog.ps.gz

[0202] The Term Processor Generator Kimwitu—van Eijk, Belinfante, Eertink. (1997) wwwtios.cs.utwente.nl/kimwitu/tacas97.ps.gz

[0203] Security Engineering of Lattice-Based Policies—Bryce (1997) set.gmd.de/˜kuehnhsr/CWASAR/D06.1.ann5.ps.gz

[0204] A scheme for adaptive biasing in importance sampling—Heegaard (1997) www.idt.unit.no/˜poulh/publications/IS-adaptive.ps www.item.ntnu.no/˜poulh/publications/adapt-scheme-abstract.ps

[0205] Towards the Industrial Use of Validation.—Ek, Grabowski. www.itm.mu-luebeck.de/publications/A-97-03/SDL-Forum-97.ps.gz

[0206] A Browser for a Versioned Entity-Relationship Database—Gulla (1992) www.idt.unit.no/˜epos/Papers/browser.ps

[0207] The Eternal Resource Locator: An Alternative Means of.—Vaclav www.usenix.org/publications/library/proceedings/ec98/full_papers/anderson/anderson.pdf

[0208] A Continuously Available and Highly Scalable.—Hvasshovd. (1991) www.idi.ntnu.no/IDT/grupper/DB-grp/tech_papers/hpts91.ps

[0209] A Parallel Implementation of XTP on Transputers—Braun, Zitterbart (1991) www.iam.unibe.ch/˜braun/lit/lcn16_xtp.ps.gz

[0210] Stublets: A Notion for Mobility-Aware Application Adaption—Dietmar Kottmann Christian (1996) ftp.diku.dk/diku/distlab/wmr96/sommer.ps.gz

[0211] ATM Traffic Measurements and Analysis on a Real Testbed—Molnár, Cselényi,. (1996) hsnlab.ttt.bme.hu/˜molnar/files/itc2.ps.gz

[0212] A CORBA Platform for Component Groupware—Hofte, van der Lugt, Bakker (1996) www.telin.nl/publicaties/1996/ozchi96.pdf

[0213] The European Web Index: An Internet Search Service for.—Lundberg, Ardö. (1996) www.lub.lu.se/desire/radar/reports/D3.12/D3.12.v1.0.ps

[0214] Results Of The CEO Project WWW Management—Hazewinkel, Van Hengstum, Pras (1996) wwwsnmp.cs.utwente.nl/nm/research/results/publications/pras/WWW.pdf

[0215] Towards Integrated QoS Management—Schmidt, Zitterbart (1995) www.telematik.informatik.uni-karlsruhe.de/˜schmidt/schmidt_hipp94.ps.gz

[0216] On engineering support for business process modelling.—Franken, de Weger. (1996) wwwhome.cs.utwente.nl/˜pires/publications/bpr96.pdf

[0217] Optimization of Spatial Joins Using Filters—Veenhof, Apers, Houtsma (1995) wwwis.cs.utwente.nl:8080/isdoc/confpaper/veenhof.BNCOD95.accepted.ps.gz

[0218] Software Architecture of Ubiquitous Scientific Computing.—Tzvetan Drashansky (1995) www.cs.purdue.edu/homes/saw/publications/95/ubiq-pses.ps

[0219] Wavefront implementation of Self Organizing Maps on RENNS—Gaute Myklebust (1995) www.idt.unit.no/˜gautemyk/icdsp95.ps

[0220] On the Enterprise Modelling of an—Educational Information. www.ub.utwente.nl/webdocs/ctit/1/0000002f.pdf

[0221] VBR Video Source Characterization And A Practical.—Cselényi, Molnár hsnlab.ttt.bme.hu/˜molnar/files/VBRtelsys.ps.gz

[0222] Use of the CANTOR system for collaborative learning in.—Hans Andersen Verner newmedia.colorado.edu/cscl/270.pdf

[0223] Jgroup/ARM: A Distributed Object Group Platform.—Meling, Montresor,. www.CS.UniBO.it/babaoglu/papers/jgroup-arm.pdf

[0224] Validation of the Open Service Access API for UMTS.—Maarten Wegdam Dirk-Jaap arch.cs.utwente.nl/publications/papers/proms01-osa-lncs22130210.pdf

[0225] A Hyperlink-Proposal Mechanism to Exemplify Cognitive.—Haffner, Roth, Meinel www.informatik.uni-trier.de/˜meinel/papers/Paper02.ps

[0226] Digital Signatures For Automobiles?!—Gollan, Meinel www.informatik.uni-trier.de/˜meinel/papers/DigitalSignaturesAuto02.pdf

[0227] Designing Safe Smart Home Systems for Vulnerable People—Dewsbury, Taylor www.smartthinking.ukideas.com/_DIRC.pdf

[0228] Providing X.509-based user—Access Control To ftp.polito.it/pub/security/papers/sec98/sec98.ps.gz

[0229] Seeing Speech In Space And Time: Psychological And.—Ruth Campbell Department www.asel.udel.edu/icslp/cdrom/vol3/1008/a1008.pdf

[0230] The Process of Designing Appropriate Smart Homes: Including.—Guy Dewsbury Bruce www.smartthinking.ukideas.com/Dewsbury_et_al_Appropriate_design_of_smart_homes.pdf

[0231] Transparent Dynamic Reconfiguration for CORBA—Almeida, Wegdam, van. (2001) www.cs.utwente.nl/˜alme/cvitae/doa01.pdf

[0232] Dissemination of Mutable Sets of Web Objects—Buchholz, Goebel, Schill, Ziegert (2001) wwwrn.inf.tu-dresden.de/˜buchholz/askom/PDCS2001.pdf

[0233] How to Support the Negotiation of Service Level Agreements.—Köppel, Böning, Abeck (1999) www.cooperation-management.de/publikationen/paper/isas99_Abeck-Boening-Koeppel.pdf

[0234] PAMINA: A Certificate Based Privilege Management System—Nochta, Ebinger, Abeck (2002) www.isoc.org/isoc/conferences/ndss/02/proceedings/papers/nochta.pdf

[0235] Modeling IT Operations to Derive Provider Accepted Management.—Abeck, Mayerl (1999) www.cooperation-management.de/publikationen/paper/im99_abeck-mayerl.pdf

[0236] On deriving rules for nativised pronunciation in.—Trancoso, Viana. (1999) www.12f.inesc.pt/documents/papers/Trancoso99b.pdf

[0237] A CANDLE to light the way?—Sebastian Abeck Jodok www.cooperation-management.de/publikationen/paper/ACandletoLightTheWay.pdf

[0238] Internet Agents for Telemedicine Services—Mea, Roberto, Conti, Di. (1999) www.telemed.uniud.it/papers/VDM-MI99.pdf

[0239] Supporting Secure and Transparent Delegation in the CORBA.—Zoltn Nochta Taufiq (2001) www.cooperation-management.de/publikationen/paper/pwc2001_nrr_cr.pdf

[0240] The adaptation and use of a WWW-based coursemanagement system.—De Boer, Collis (2000) www.ub.utwente.nl/webdocs/ctit/1/00000059.pdf

[0241] Evaluation of Mobile Agent Systems with Respect to Failure.—Otto Wittner October www.item.ntnu.no/˜ottow/papers/failsemMASreport.pdf

[0242] Proactive Services in a Distributed Traffic Telematics.—Gura, Held, Kaiser www.informatik.uni-ulm.de/rs/projekte/core/ProctiveServ.pdf

[0243] TCP over GPRS—Performance Analysis—Manner (1999) www.cs.helsinki.fi/u/jmanner/papers/Thesis-Manner.ps

[0244] Ip Over Wavelength-Routed Access Networks—Marcos Rogrio Salvador wwwctit.cs.utwente.nl/˜salvador/Eunice99.pdf

[0245] Increasing Retrievability and Reusability of Learning.—Hiddink Van Der www.ub.utwente.nl/webdocs/ctit/1/00000056.pdf

[0246] Experiences from Development of Home Health Care Applications.—Leili Lind Erik ftp.imt.liu.se/pub/bildb/MIpapers/524_LIND.PDF

[0247] A Review of Parallel Implementations of Backpropagation.—Torresen, Tomita www.ifi.uio.no/˜jimtoer/chp2.ps

[0248] ESCORT: Towards Integration in Intersection Control—Andrea Savigni Filippo (2000) www.cs.ucl.ac.uk/staff/A.Savigni/papers/2000_jubilee_escort_roma.pdf

[0249] Usability Field-Test Of A Spoken Data-Entry System—Marcello Federico And poseidon.itc.it:7117/˜ssi/DITELO/papers/ICASSP99_—1.ps

[0250] FLAMINGO: A Packet-switched IP over WDM Metro Optical Network—Dey Koonen Geuzebroek (2001) wwwctit.cs.utwente.nl/˜salvador/NOC2001.pdf

[0251] Real-time test specification with TTCN-3—Dai, Grabowski, Neukirchen (2001) www.itm.mu-luebeck.de/publications/FBT2001/Abstract_fbt01neukdai.pdf

[0252] A System for Uniform and Multilingual Access to Structured.—Xu, Netter, Stenzhorn (2000) www.cs.ust.hk/acl2000/Demo/04_xu.pdf

[0253] Corpus-driven learning of Event Recognition Rules—Roberto Basili Maria www.dcs.shef ac.uk/˜fabio/ML4IE/2.PS.gz

[0254] Web-Support for Activating Use of Theory in Group-Based Learning—Jan Van Der www.ub.utwente.nl/webdocs/ctit/1/0000005a.pdf

[0255] Automated Generation of Category-Specific Thesauri for.—Attardi, Di Marco. (1998) faure.iei.pi.cnr.it/˜fabrizio/Publications/TR0698.ps

[0256] The use of CMC in applied social science training—Interim Report Merja www.stir.ac.uk/schema/deliverables/D5.3.pdf

[0257] The IT-Potential Of Haptics—Touch access for people with.—Sjöström (1999) www.certec.lth.se/doc/touchaccess/TouchAccess.pdf

[0258] An All-Optical WDM Packet-Switched Network Architecture.—Marcos Rogrio Salvador (2001) wwwctit.cs.utwente.nl/˜salvador/ICN2001.pdf

[0259] An Adaptive, Collaborative Environment to Develop.—Vizcano. oreto.inf-cr.uclm.es/personas/avizcaino/itsenv.ps

[0260] The HyperMuseum Theme Generator System: Ontology based.—Stuer, Meersman, De. (2001) www.archimuse.com/mw2001/papers/stuer/stuer.html http ://wise.vub.ac.be/Download/Papers/stuerMW2001.pdf

[0261] Failure Semantics of Mobile Agent Systems Involved in.—Otto Wittner Carsten (1999) www.item.ntnu.no/˜ottow/papers/failsemNIK99.pdf

[0262] Cross-Entropy Guided Mobile Agents Finding Cyclic Paths in.—Wittner, Helvik (2002) www.item.ntnu.no/˜wittner/aamas2002_submitted.pdf

[0263] Cross Entropy Guided Ant-like Agents Finding Dependable.—Wittner, Helvik (2002) www.item.ntnu.no/˜wittner/cec2002.pdf

[0264] Using Information Flow Control to Evaluate Access.—Mantel, Schairer,. www.dfki.de/˜schairer/publications/report00159.ps.gz

[0265] Network Architecture of a Packet-switched WDM LAN/MAN—Dey Koonen And (2000) wwwctit.cs.utwente.nl/˜salvador/LEOS2000.pdf

[0266] Specification and Validation of a Real-Time Parallel.—de Farias, Pires. (1997) www.ub.utwente.nl/webdocs/ctit/1/00000066.pdf

[0267] Mobile Ip: Security Application—Tuquerres, Salvador, Sprenkels ntrg.cs.tcd.ie/htewari/papers/MobileIP-Sec.pdf

[0268] M3POC: a multimedia multicast transport protocol for cooperative.—Owezarski www.laas.fr/˜owe/PUBLIS/99525.ps.gz

[0269] User Interfaces for All—Kobsa, (eds.) (1999) www.gmd.de/publications/report/0074/Text.pdf

[0270] Supporting PIM-SM in All-Optical Lambda-Switched Networks—Marcos Rogrio Salvador (2001) wwwctit.cs.utwente.nl/˜salvador/SBRC2001.pdf

[0271] Managing Distributed Personal Firewalls with Smart.—Haffner, Roth, Heuer, www.informatik.uni-trier.de/˜meinel/papers/Managing01.ps

[0272] FINAL REPORT: LAURIN http://laurin.uibk.ac.at/-Version November Author germanistik.uibk.ac.at/laurin/reports/finalrep01.pdf

[0273] Some Implications of MSC, SDL and TTCN Time Extensions.—Hogrefe, Koch. (2001) www.itm.mu-luebeck.de/publications/DH_BK_HN_—2001_SDLForum/sdlforum2001.pdf

[0274] Supporting IP Dense Mode Multicast Routing Protocols in.—Marcos Rogerio Salvador (2000) wwwctit.cs.utwente.nl/˜salvador/OPTICOMM2000.pdf

[0275] Report on the course for Technology Teachers WWW Course of.—Jyrki Pulkkinen And telematics.ex.ac.uk/T3/0/downloads/d13-1.pdf

[0276] A Multi-DSP Laboratory Course—Rinner, Schneider, Steger, Weiss www.iti.tu-graz.ac.at/de/people/schneider/papers/rinner98.pdf

[0277] Modularity—A Concept For New Neural Network Architectures—Schmidt, Bandar (1998) www.comp.lancs.ac.uk/˜albrecht/pubs/pdf/schmidt_csa_irbid_—1998.pdf

[0278] Supporting IP Dense Mode Multicast Routing in All-Optical.—Marcos Rogrio Salvador (2001) wwwctit.cs.utwente.nl/˜salvador/ONM2001.pdf

[0279] Dagstuhl Seminar on Ubiquitous Computing—September The International (2001) www.inf.ethz.ch/vs/events/dag2001/intro/DagstuhlIntroductions.pdf

[0280] A Framework For Video Modelling—Centre For Telematics www.cs.utwente.nl/˜milan/docs/innsb.ps

[0281] Conceptual Stage in Designing Multimedia for Tele Learning—Kommers (2001) www.ub.utwente.nl/webdocs/ctit/1/00000060.pdf

[0282] Signed Preservation Of Online References—Heuer, Losemann, Meinel www.informatik.uni-trier.de/˜meinel/papers/webnet00b.ps

[0283] Chapter 7 Implementation of Backpropagation Neural.—Jim Torresen Department www.ifi.uio.no/˜jimtoer/chp3.ps

[0284] TIMe at a glance—Braek, Gorman, Haugen, Melby. www.sintef.no/time/report.pdf

[0285] Executive Summary—The Vision Of www.it.bton.ac.uk/research/seake/knowledge.pdf

[0286] Supporting the Travelling Tradition: A report on the work.—Ken Marks Department (2000) ui4all.ics.forth.gr/i3SD2000/Marks.PDF

[0287] Circuits and Systems—Benini, De Micheli, Macii, Maloberti www.nd.edu/˜stjoseph/newscas/CASMagvol1no1.pdf

[0288] Enterprise Modelling For An Educational Information.—Ing Widya Cees (2001) wwwhome.cs.utwente.nl/˜widya/webpapers/iceis2001_—205.pdf

[0289] Telematics For Group-Based Learning: Simplicity Versus.—van der Veen, Collis. www.ub.utwente.nl/webdocs/ctit/1/00000057.pdf

[0290] Research Report 1997—1999—Department Of Computer (1997) www.cs.ucy.ac.cy/Research/archives/rr97-99.ps

[0291] Translation Resources, Merging Strategies and Relevance.—Djoerd Hiemstra Wessel janus.cs.utwente.nl/˜hiemstra/papers/clefl.pdf

[0292] An Information System for Long-distance Cooperation in Medicine.—Kosch, al. (2000) www.ii.uib.no/para2000/program/jacek.ps

[0293] Next Generation Internet in Europe—Published By The www.infowin.org/ACTS/ANALYSYS/PRODUCTS/THEMATIC/NGI/ngi_in_europe.pdf

[0294] R. Mu˜noz, M. Saiz-Noeda, A. Su arez and M. Palomar—Grupo De Investigaci (2000) gplsi.dlsi.ua.es/gplsi/articulos/a2000/mt2000.ps

[0295] Lazy Users and Automatic Video Retrieval Tools in (the) Lowlands—The Lowlands Team carol.wins.uva.nl/˜cgmsnoek/pub/trec10video.pdf

[0296] Remote MIB item look-up service—Pras, Boros, Helthuis (2002) www.simpleweb.org/nm/research/results/publications/pras/2002-04-noms.pdf

[0297] Use Of Real And Contaminated Speech For Training Of A.—Matassoni Omologo And (2001) poseidon.itc.it:7117/˜ssi/SHINE/ps/eurospeech01.ps.gz

[0298] Extending the Data Storage Capabilities of a Java-based.—Clemens Cap Nico wwwiuk.informatik.uni-rostock.de/˜maibaum/docs/maibtune.ps

[0299] Towards Precision Tools For ATM Network Design, Dimensioning.—Molnár, al. hsnlab.ttt.bme.hu/˜molnar/files/peripol.ps.gz

[0300] Fair Bandwidth Allocation of a Wireless Base Station—Gyorgy Mikl'os Traffic hsnlab.ttt.bme.hu/˜molnar/files/iqwim99.ps.gz

[0301] Forecasting the Success of Telecommunication Services in.—Detlef Schoder. (2000) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/Sc2000.pdf

[0302] A General Fractal Model of Internet Traffic—Molnar hsnlab.ttt.bme.hu/˜molnar/files/multifractalLCN.pdf

[0303] Correlations in ATM Cell Streams Exposed to Cell Delay Variation—Molnár, Blaabjerg hsnlab.ttt.bme.hu/˜molnar/files/hung1.ps.gz

[0304] A General Traffic Control Framework in ATM Networks—Fodor, Marosits, Molnár (1996) hsnlab.ttt.bme.hu/˜molnar/files/gtf.ps.gz

[0305] NAVIGATION IN CYBERSPACE Using Multi-Dimensional Scaling.—Schoder Institut Fur (1999) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/Sc1999a.pdf

[0306] Performance Measurement Tool for Packet Forwarding Devices—Tam As Kovacshazy www.mit.bme.hu/˜khazy/publications/imtc2001_—3472.pdf

[0307] Benefits of a Universal Security Framework—Report By Arnd (2000) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/We2000f.pdf

[0308] Methods for Computing B-ISDN Link Blocking Probabilities—Molnár, Blaabjerg hsnlab.ttt.bme.hu/˜molnar/files/link.ps.gz

[0309] Inter-organizational Networking of Small and.—Framework And. (1999) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/EgEn1999.pdf

[0310] Using Objects and Patterns to Implement Domain Ontologies—Guizzardi, Falbo, Filho (2001) wwwhome.cs.utwente.nl/˜guizzard/jbcs.pdf

[0311] Highly Secure Low-cost Computers—Arnd Weber Today's (2000) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/We2000e.pdf

[0312] On Modeling and Shaping Self-Similar ATM Traffic—Andor Molnár And hsnlab.ttt.bme.hu/˜molnar/files/itc97.ps.gz

[0313] Pitfalls in Long Range Dependence Testing and Estimation—Molnar, Dang hsnlab.ttt.bme.hu/˜molnar/files/pitfalls.pdf.gz

[0314] Distributed Fair Bandwidth Allocation of a Wireless Base.—Gyorgy Miklos Traffic (2000) hsnlab.ttt.bme.hu/˜molnar/files/netw00.ps.gz

[0315] Highly Secure Low-cost PDA-phones—Weber (2000) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/We2000d.pdf

[0316] Sharing Telematics Courses—The CANDLE project—Aiko Pras Centre (2001) www.simpleweb.org/nm/research/results/publications/pras/2001-09-04-eunice.pdf

[0317] A Prototype for an Agent-based Secure Electronic.—Padovan, Sackmann. (2001) www.iig.uni-freiburg.de/telematik/forschung/projekte/e_sicherheit/comet/publikationen/PaSaEyPi2000.pdf

[0318] On Measurements of Multimedia Traffic in ATM Networks—Cselényi. hsnlab.ttt.bme.hu/˜-molnar/files/icomt.ps.gz

[0319] Advanced Generation Tool of Application's Network Traffic—Petroczi, Molnar hsnlab.ttt.bme.hu/˜molnar/files/agentant.ps.gz

[0320] On Burst And Correlation Structure of Teletraffic Models—Molnár, Miklós hsnlab.ttt.bme.hu/˜molnar/files/ilkley97.ps.gz

[0321] Scaling Analysis of IP Traffic Components—Molnar, Dang (2000) hsnlab.m.bme.hu/˜molnar/files/itcssip00.ps.gz

[0322] A System for Supporting Cross-Lingual Information Retrieval—Capstick, al. (1999) speech.ftw.at/˜gor/pub/ipm/mulinex-ipm99.pdf

[0323] Spatiotemporal Segmentation and Tracking of Objects for.—Kompatsiaris, Strintzis (2000) egnatia.ee.auth.gr/˜ikom/CSVT2000.pdf

[0324] Region-Based Color Image Indexing And Retrieval—Ioannis Kompatsiaris Evagelia (2001) egnatia.ee.auth.gr/˜ikom/icip2001.pdf

[0325] Kompatsiaris—And Michael Strintzis egnatia.ee.auth.gr/˜ikom/ICIP00.pdf

[0326] th IFLA Council and General Conference Aug. 16-25, 2001—Code Number Division www.ifla.org/IV/ifla67/papers/161-165e.pdf

[0327] Agent-Mediators In Media-On-Demand Eletronic Commerce—Joo Paulo Andrade wwwhome.cs.utwente.nl/˜guizzard/mod-amec-cuba.pdf

[0328] A Web-based Distributed Environment to Support Teleteaching:.—Ch Bouras Computer ru6.cti.gr/Publications/261.pdf

[0329] Web-Enabled Distance Education Environment—Bouras, Lampsas, Bazaios. (1998) ru6.cti.gr/Publications/296.pdf

[0330] ID-No. of presentation: t3a01391—Authors Christos Bouras ru6.cti.gr/Publications/279.pdf

[0331] Usability meets Security—The Identity-Manager as your.—Jendricke, Markotten (2000) www.acsac.org/2000/papers/90.pdf

[0332] Deployment Scenarios of DVEs in Education—Bouras Computer Technology ru6.cti.gr/Publications/324.pdf

[0333] Trends: Training Educators Through Networks And.—Christos Bouras Computer (1996) ru6.cti.gr/Publications/439.pdf

[0334] On-Demand Hypermedia/Multimedia Service over.—Bouras, Kapoulas. (1996) ru6.cti.gr/Publications/358.pdf

[0335] Tele-working services from the Greek PTT—Christos Bouras Vaggelis (1999) ru6.cti.gr/Publications/322.pdf

[0336] HIPPOCRATES : A Tool for Distance Education—Bouras Fotakis Kapoulas ru6.cti.gr/Publications/305.pdf

[0337] A Platform for the Implementation of the Services.—Bouras, Gkamas. (1998) ru6.cti.gr/Publications/259.pdf

[0338] Training Centres : An Architecture for the Realisation.—Christos Bouras Computer ru6.cti.gr/Publications/292.pdf

[0339] In-Service Training through ODL Environments: From User.—Bouras Lampsas Spirakis ru6.cti.gr/Publications/275.pdf

[0340] Distributed Learning Environment using Advanced Services.—Ch Bouras Computer (1999) ru6.cti.gr/Publications/453.pdf

[0341] Routing Management Application Based On Mobile Agents On.—Anglica Reyes Ernesto wwwtgs.cs.utwente.nl/eunice/summerschool/papers/paper9-2.pdf

[0342] Quality Of Service Monitoring In Ip Networks By Using.—Tams Varga Andrs wwwtgs.cs.utwente.nl/eunice/summerschool/papers/paper4-3.pdf

[0343] Issues on QoS based Routing in the Integrated Services.—Gbor Rtvri Department wwwtgs.cs.utwente.nl/eunice/summerschool/papers/paper4-1.pdf

[0344] Usability Research in a Housing Fair: Problems and.—Sajaniemi, Tossavainen (1995) csjoensuu.fi/pub/Reports/A-1995-7.ps.gz

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[0347] The Catallaxy as a new Paradigm for the Design of.—Eymann, Padovan, Schoder (2000) www.iig.uni-freiburg.de/telematik/forschung/publikationen/pubfiles/EyPaSc2000.pdf

[0348] Internet Accounting—Pras, van Beijnum, Sprenkels. (2001) www.simpleweb.org/nm/research/results/publications/pras/internet-accounting.pdf

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[0352] A Model to Evaluate Certificate Revocation—Forn Castro Department (2000) www-mat.upc.es/˜jforne/jf_SCI2000_—1.pdf

[0353] Dublin Bus Tracking Service—Design and implementation of a.—Fallon (2000) ftp.cs.tcd.ie/pub/tech-reports/reports.00/TCD-CS-2000-47.pdf

[0354] Integrating Different Strategies for Cross-Language.—Buitelaar, Netter, Xu www.dfki.de/lt/mietta/mietta-twlt.ps

[0355] Integrating Trading and Load Balancing for Efficient.—Thiβen, Neukirchen (2000) www.itm.mu-luebeck.de/publications/DT_HN_—2000_ITaLBfEMoSiDS/USM2000.pdf

[0356] Junction Point Aspect: A Solution to Simplify Implementation of.—Berger (2000) micado.project.free.fr/Publi/ecoop2000.ps.gz

[0357] Csaba Antal—Jzsef Molnr Sndor www.cs.kau.se/˜soren/dkdoc/documentstore/cc_fp.ps

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[0359] Z39.50 Application programmer's Interface SYSTEM.—Document No Document ftp.ddb.de/pub/dbvosi/ses_v3.ps.gz

[0360] Hardware Implementation of a Secure Bridge in Ethernet.—Forn Soriano Mels www-mat.upc.es/˜jforne/jf_GLOBECOM93.pdf

[0361] Performance Evaluation of Strategies for Integration.—Queija, van den Berg,. (1999) www.cwi.nl/ftp/CWIreports/PNA/PNA-R9903.ps.Z

[0362] Inverse Multiplexing for ATM. Operation.—Aguilar-Igartua. (1999) marley.upc.es/pub/articles/icatm99.pdf

[0363] An integrated solution for secure communications over B-ISDN—Forn Mels Department www-mat.upc.es/˜jforne/jf_CMS96.pdf

[0364] Web Representation with Dynamic Thumbnails—Schmid www.comp.lancs.ac.uk/computing/users/sschmid/Yuforic/YuforicExtAbstr.ps

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[0366] Sojourn Times in Non-Homogeneous QBD Processes with Processor.—Queija (1999) www.cwi.nl/ftp/CWIreports/PNA/PNA-R9901.ps.Z

[0367] A guided tour through LGM—How to generate spoken.—Krahmer, Landsbergen. www.ipo.tue.nl/homepages/ekrahmer/Pubs/lgm.ps

[0368] Verifying a Smart Design of TCAP—Arts, van Langevelde (1999) www.cwi.nl/ftp/CWIreports/SEN/SEN-R9910.ps.Z

[0369] Securing Multimedia Applications over B-ISDN—Jordi Forn Mels www-mat.upc.es/˜jforne/jf_PROMS96.pdf

[0370] Teaching and learning with the WWW in the undergraduate.—Oliver, Omari, Cowan elrond.scam.ecu.edu.au/oliver/docs/96/AUSWEB2d.pdf

[0371] Toward a Standard for Guideline Representation: an.—Domenico Pisanelli Aldo saussure.irmkant.rm.cnr.it/onto/publ/amia99/amia99.pdf

[0372] Time Domain MLE of the Parameters of FBM Traffic—Vidács, Virtamo (1999) keskus.tct.hut.fi/tutkimus/com2/publ/fbm2.pdf

[0373] Artificial Coordination—Simulating Organizational.—Eymann, Padovan, Schoder (1998) www.iig.uni-freiburg.de/˜padovan/publications/cefes98.pdf

[0374] REMOT-A Project to Remotely Monitor and Control Scientific—Experiments Pucillo Oat www.aps.anl.gov/icalepcs97/paper97/p235.pdf

[0375] Performability Analysis of Markov Reward Models with Rate and.—Andor Acz And (1999) webspn.hit.bme.hu/˜telek/cikkek/racz99a.ps.gz

[0376] Analysis of the Completion Time of Markov Reward Models.—Mikl'os Telek Andr'as webspn.hit.bme.hu/˜telek/cikkek/tele98b.ps.gz

[0377] A New Method for Spectral Shaping Coding—Peter Amos Aszl'o webspn.hit.bme.hu/˜telek/cikkek/vamo98a.ps.gz

[0378] MRMSolve: A Tool for Transient Analysis of Large Markov.—Rácz, Tóth, Telek webspn.hit.bme.hu/˜telek/cikkek/racz00f.ps.gz

[0379] Managing Services in Distributed Systems by Integrating.—Thiβen, Neukirchen (2000) www.itm.mu-luebeck.de/publications/ISCC2000/ISCC2000.pdf.gz

[0380] Conformance Testing with TTCN—Schieferdecker, Grabowski (2000) www.itm.mu-luebeck.de/publications/I_J_—2000_CTwT/Telektronnikk4_—2000_CTandTTCN.pdf

[0381] Analysis and Modelling of Collaborative Learning Interactions—Workshop Notes (2000) collide.informatik.uni-duisburg.de/˜martin/publication/Muehlenbrock-ECAI-2000.pdf

[0382] Aligning IT and Organization in the MediaSite project—Iacucci, Axelsson (2000) iris23.htu.se/proceedings/PDF/20final.PDF

[0383] Enriching Textual Documents with Time-codes from Video.—van der Sluis, de Jong (2000) 133.23.229.11/˜ysuzuki/Proceedingsall/RIAO2000/Wednesday/37CP1.ps

[0384] Modular Automated Transport—Frequently Asked Questions (FAQ)—Schweizer (2000) circwww.epfl.ch/staff/joerg/mat/doc/faq/faq.ps

[0385] The CIMI Profile Release 1.0H—Profile For Cultural www.cimi.org/public_docs/HarmonizedProfile/CIMIProfile10H.pdf

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[0387] Analysis of a Distributed Wireless Fair Scheduling Scheme—Miklós hsnlab.ttt.bme.hu/˜molnar/files/itcssmob00.ps.gz

[0388] CAC Algorithm Based on Advanced Round Robin Method for QoS.—Marosits, Molnár hsnlab.ttt.bme.hu/˜molnar/files/iscc01.pdf.gz

[0389] Link Capacity Sharing Between Guaranteed- and Best Effort.—Rácz, Telek webspn.hit.bme.hu/˜telek/cikkek/racz01a.ps.gz

[0390] Quality of Service on the Internet: Evaluation of the.—Elisabete Reis Elreis (2001) dragao.co.it.pt/conftele2001proc/pap101.pdf

[0391] A MixDemonstrator for teaching Security in the Virtual.—Jendricke, Rannenberg www.scis.cowan.edu.au/research/wise/WISE1Proceedings/pdf/jendricke.pdf

[0392] Fair Allocation Of Elastic Traffic For A Wireless Base Station—Gyorgy Miklos Traffic (1999) hsnlab.ttt.bme.hu/˜molnar/files/globe99.ps.gz

[0393] Cell Delay Variation in an ATM Multiplexer—Molnár, Blaabjerg hsnlab.ttt.bme.hu/˜molnar/files/cdvsnew.ps.gz

[0394] Supporting All Service Classes in ATM: A Novel.—Marosits. (1999) hsnlab.ttt.bme.hu/˜molnar/files/info99.ps.gz

[0395] The Impact Of Long Range Dependence On Cell Loss In An.—Vidacs, Molnar, Gordos (1998) hsnlab.ttt.bme.hu/˜molnar/files/globe98.ps.gz

[0396] Investigation of Fractal Properties in Data Traffic—Dinh, Molnár. hsnlab.ttt.bme.hu/˜molnar/files/jc98.ps.gz

[0397] Performance Evaluation of a General Traffic Control.—Marosits. hsnlab.ttt.bme.hu/˜molnar/files/ipccc99.ps.gz

[0398] The Demand for Stored Value Payment Instruments—Ingo Pippow Detlef (2001) www.iig.uni-freiburg.de/telematik/forschung/projekte/e_sicherheit/comet/publikationen/PiScho2001.pdf

[0399] On The Effects Of Non-Stationarity In Long-Range Dependence Tests—Trang Dinh And hsnlab.ttt.bme.hu/˜molnar/files/trendeff.ps.gz

[0400] Bottlenecks on the Way Towards Fractal Characterization of.—Andor Moln'ar Attila hsnlab.ttt.bme.hu/˜molnar/files/pmccn97.ps.gz

[0401] Multimedia Databases in Education—Gerrit Hiddink Centre wwwhome.ctit.utwente.nl/˜hiddinkg/professional/papers/dolls97.ps

[0402] Content-based video retrieval—Petkovic (2000) www.edbt2000.uni-konstanz.de/phd-workshop/papers/Petkovic.pdf

[0403] Adaptive Optimisation of Importance Sampling for.—Heegaard (1996) www.idi.ntnu.no/˜poulh/publications/nts13a.ps

[0404] Factors of reuse of Units of Learning Material—Gerrit Hiddink Centre wwwhome.ctit.utwente.nl/˜hiddinkg/professional/papers/reuse.ps

[0405] Multilateral Security A concept and examples for balanced security—Rannenberg (2000) csrc.nist.gov/nissc/2000/proceedings/papers/202ra.pdf

[0406] Educational Multimedia Databases: Past and Present—Gerrit Hiddink Centre wwwhome.ctit.utwente.nl/˜hiddinkg/professional/papers/systems.ps

[0407] Resource-limited information retrieval in Web-based.—Daan Velthausz And (1997) www.trc.nl/publicaties/1997/reslim/resource-limited.pdf

[0408] CRL supported a smart redesign of a real-life protocol—Thomas Arts Email extranet.telin.nl/dscgi/ds.py/Get/File-8309/fmics99.ps.Z

[0409] Convergence In The Digital Age—Table Of Content ftp.cordis.lu/pub/libraries/docs/proceedings.pdf

[0410] Using Automated Assistance Systems—Putting The Driver Into Focus—Reichardt (1998) www.daimler-benz.com/research/events/pdf/IV980240.PDF

[0411] The Cave-Wp4 Generic Speaker Verification System—Jaboulet, KOOLWAAIJ. (1998) www.ubilab.org/publications/print_versions/pdf/jab98.pdf

[0412] Field Test Of A Calling Card Service Based On.—den Os, Boves. www.ubilab.org/publications/print_versions/pdf/den97.pdf

[0413] Distributed Electronic Commerce Systems—Sonja Zwil Er ftp.cs.umass.edu/pub/net/pub/hgschulz/i96/zwissler.ps.gz

[0414] Needed Services For Network Performance Evaluation—Dung Dinh Luong gollum.ttt.bme.hu/˜luong/tools/atmip.ps

[0415] Link Proposals with Case-Based Reasoning Techniques—Haffner, Roth, Heuer. www.ti.fhg.de/conferences/200011171414080.ps

[0416] Remote Access to Medical Records via the Internet: Feasibility,.—Pj Lees Ce (1999) www.ics.forth.gr/ICS/acti/cmi_hta/publications/papers/1999/cic99/lees_cic99.pdf

[0417] Partial Methods Versus End-to-End Measurements—Dung Dinh Luong gollum.ttt.bme.hu/˜luong/tools/ifip.ps

[0418] The Role of Packet-dropping Mechanisms in QoS Differentiation—Goncalo Quadros Antonio (2000) www.dei.uc.pt/˜boavida/papers/2000icon.pdf

[0419] Component-Based Groupware Tailorability using Monitoring.—de Farias, Diakov (2000) amidst.ctit.utwente.nl/publications/cscw_cbg2000.pdf

[0420] Modeling of Time and Document Aging for Request.—Haffner, Roth, Engel,. (2000) www.ti.fhg.de/conferences/200009211730520.ps

[0421] Mpeg-4 Authoring Tool For The Composition Of 3D.—Daras. (2001) egnatia.ee.auth.gr/˜ikom/ISCAS2001.pdf

[0422] Disambiguation Strategies for Cross-language Information.—Djoerd Hiemstra And (1999) www.cs.utwente.nl/˜hiemstra/papers/ecdl99.ps

[0423] the IFLA Council and General Conference Aug. 16-25, 2001—Code Number Division www.ifla.org/IV/ifla67/papers/161-165e.pdf

[0424] CANDLE: an European E-Education project to . . . —Batlogg, al. (2000) www.ssgrr.it/en/ssgrr2000/papers/164.pdf

[0425] State-dependent M/G/1 Type Queueing Analysis for.—Altman. (2000) www.cwi.nl/ftp/CWIreports/PNA/PNA-R0005.ps.Z

[0426] Continuous Queries within an Architecture for Querying.—Brinkhoff, Weitkämper (2001) www.fh-wilhelmshaven.de/oow/institute/iapg/personen/brinkhoff/paper/SSTD2001.pdf

[0427] The Distribution And Partitioning Scheme Of The.—Jiménez. ches.ing.ula.ve/INVESTIGACION/ARTICULOS/TANIA/SIM-71.ps.gz

[0428] An Architecture For Video On Demand Agent-Mediated.—Almeida, Guizzardi. wwwhome.cs.utwente.nl/˜guizzard/vod-amec-workcomp99.pdf

[0429] Reusing Multi-Media Components: A Catalogue Implementation—Steinmann, Shearer www.fernuni-hagen.de/DVT/Publikationen/Papers/emmsec.pdf

[0430] Multiagent Systems—Instructor Prof Dh 136.159.122.221/seminar/enmf619_—02/enmf02.pdf

[0431] Twenty-One at CLEF-2000: Translation resources, merging.—Djoerd Hiemstra Wessel www.iei.pi.cnr.it/DELOS/CLEF/twentyon.pdf

[0432] Papabiles—Torday, Bierlaire (2001) rosowww.epfl.ch/mbi/strc-papabiles.pdf

[0433] Using Objects and Patterns to Implement Domain Ontologies—Guizzardi, Filho (2001) wwwhome.cs.utwente.nl/˜guizzard/SBES2001vf.pdf

[0434] Decision Support Systems from a Health Informatics Perspective—Nykänen (2000) acta.uta.fi/pdf/951-44-4897-9.pdf

[0435] NetTrouble: A TTS for Network Management—Lus Santos Pedro www.dei.uc.pt/˜psimoes/papers/its98.pdf

[0436] Results and experience from the application of a common.—Antonis Bouras. (1998) ru6.cti.gr/Publications/318.pdf

[0437] The Informationand Communication Technologies In Education—Christos Bouras Computer ru6.cti.gr/Publications/289.pdf

[0438] Internet Protocols for Synchronous Distance Learning—Ch Bouras Computer (2000) ru6.cti.gr/Publications/431.pdf

[0439] The Euro in the Electronic Purse—Allard, Alyankian, Ankri, Collin. (2000) www.eurosmart.com/download/WhitePaper.pdf

[0440] Monitoring Extensions for Component-Based Distributed.—Diakov, van Sinderen. (2000) amidst.ctit.utwente.nl/publications/proms2000.pdf

[0441] The Q-bit Scheme—Congestion Avoidance Using (1992) gatekeeper.dec.com/pub/doc/sigcomm/ccr/archive/1992/apr92/qbit.ps.Z

[0442] Performance of a Parallel Transport Subsystem Implementation—Torsten Braun Institute www.iam.unibe.ch/˜braun/lit/hpcs93.ps.gz

[0443] Towards Dynamic Composition of Hybrid Communication Services—Floch, Braek (2000) www.item.ntnu.no/˜jacf/paper/smarnett2000.pdf

[0444] Optimising the Operation of the World Wide Web in.—Hadjiefthymiades. www.cs.auc.dk/˜tryfona/papers/cacherel.ps

[0445] Generating Test Cases for Infinite System Specifications—Stefan Heymer And www.itm.mu-luebeck.de/publications/GTCfISS/HeymerGrabowski.ps.gz

[0446] Computational Perspectives on Discourse and Dialogue—Bonnie Lynn Webber www.dai.ed.ac.uk/daidb/people/homes/bonnie/handbook.ps.gz

[0447] Virtual Universities—Ebner, Hogrefe (1999) www.itm.mu-luebeck.de/publications/VFH/ebner_hogrefe_waki99.ps.gz

[0448] Compensation methods to support generic graph editing: A case.—Even, Spelt wwwhome.cs.utwente.nl/˜seven/ECOOPWS.pdf

[0449] Towards the Generation of Distributed Test Cases Using Petri.—Heymer, Grabowski www.itm.mu-luebeck.de/publications/FBT99/fbt99.ps.gz

[0450] Test Case Specification with Real-Time TTCN—Walter, Grabowski www.itm.mu-luebeck.de/publications/TCSwRTTTCN/WalterGrabowski.ps.gz

[0451] Scientific Approaches and Techniques for Negotiation.—Gerding, van Bragt,. www.cwi.nl/projects/TA/reports/negotiation.ps

[0452] Towards an Integrated Test Methodology for Advanced.—Grabowski, Walter www.itm.mu-luebeck.de/publications/tcs99.ps.gz

[0453] TTCN-3—A new Test Specification Language for Black-Box Testing.—Grabowski (2000) www.itm.mu-luebeck.de/publications/ttcn3/Grabowski.pdf.gz

[0454] Test Architectures for Distributed Systems—State of the Art and.—Walter (1998) www.itm.mu-luebeck.de/publications/IWTCS98TA/IWTCS98Testarchitectures.ps.gz

[0455] Asbru: A Task-Specific, Intention-Based, and.—Miksch, Shahar, Johnson ftp.ifs.tuwien.ac.at/pub/publications/mik_kem197.pdf

[0456] Protocol Specifications—Written By Jacob cmc.dsv.su.se/select/SEL-prot-spec-v11-jp-991009.pdf

[0457] Towards The Third Edition Of TTCN—Grabowski, Hogrefe (1999) www.itm.mu-luebeck.de/publications/iwtcs99.ps.gz

[0458] A Framework for the Specification of Test Cases for.—Walter, Grabowski (1999) www.itm.mu-luebeck.de/publications/Walter-Grabowski-JIST99/jist.ps.gz

[0459] Verification of Compensation Requirements for the SEPIA.—Even, Spelt (1998) wwwhome.cs.utwente.nl/˜seven/CTIT-TR-98-25.pdf

[0460] Cote de Resyste—Conformance Testing Reactive wwwtios.cs.utwente.nl/Docs/projects/cote-de-resyste/stw.ps

[0461] Long Cycles and Long Paths in the Kronecker Product of a.—Jha, Agnihotri, al. (1995) www.csjhu.edu/˜rajesh/ps/cta.ps

[0462] Tutorial on Message Sequence Charts (MSC'96)—Rudolph, Grabowski, Graubmann (1996) www.itm.mu-luebeck.de/publications/MSC96/dis-tutorial.ps.gz

[0463] The Standardization of Core INAP CS-2 by ETSI—Grabowski, Hogrefe (1999) www.itm.mu-luebeck.de/publications/CS2-Standardization.ps.gz

[0464] On The Design Of The New Testing Language TTCN-3—Grabowski, Wiles, Willcock. (2000) www.itm.mu-luebeck.de/publications/New_TTCN3/GrabowskiEtAll.pdf.gz

[0465] omVR—A Safety Training System for a Virtual Refinery—Haller, Kurka, Volkert. www.gup.uni-linz.ac.at:8001/staff/kurka/docs/ismcr99.pdf

[0466] Senior Online—Telematics De Report cmc.dsv.su.se/sol/sol-transfer-spec.pdf

[0467] Formal Methods and Conformance Testing—or—What are we.—Heymer, Grabowski www.itm.mu-luebeck.de/publications/FBT98/FBT98.ps.gz

[0468] A Theorem Prover-Based Analysis Tool for Object-Oriented Databases—Spelt, Even (1999) wwwhome.cs.utwente.nl/˜seven/CTIT-TR-98-22.pdf

[0469] Chemistry in Action: Discovering the Behaviour of a Network.—Heymer, Grabowski (1998) www.itm.mu-luebeck.de/publications/A-98-18/Report-A-98-18.ps.gz

[0470] ERP in the e-commerce era—Luttighuis, Biemans extranet.telin.nl/dscgi/ds.py/Get/File-2092/baanUSP.pdf

[0471] Business-Driven Design of Transaction Services—Biemans, Janssen, Luttighuis,. (1999) extranet.telin.nl/dscgi/ds.py/Get/File-664/ICE.pdf

[0472] Modelling organisations—Wetering (1999) extranet.telin.nl/dscgi/ds.py/Get/File-2902/modellingV2.pdf

[0473] On Wrapping Query Languages and Ecient XML Integration—Vassilis Christophides Sophie (2000) www.oasis-open.org/cover/vassilisQueryWrap.pdf

[0474] MESH Release 2 implementation at CTIT—Diakov, van Sinderen, Koprinkov amidst.ctit.utwente.nl/publications/ctit_tr99-08.pdf

[0475] EUROgatherer: a Personalised Gathering and Delivery.—Amato, Straccia, Thanos (2000) faure.iei.pi.cnr.it/%7Estraccia/download/papers/SCI2000/SCI2000.pdf

[0476] Frameworks for protocol implementation—Barbosa, Pires, van Sinderen (1998) wwwhome.cs.utwente.nl/˜sinderen/publications/sbrc98.pdf

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• [0710] M. V. Wickerhauser, “Lectures on Wavelet Packet Algorithms”
• [0711] M. V. Wickerhauser, “Smooth Localized Orthonormal Bases”
• [0712] C. Zarowski, “Notes on Orthogonal Wavelets and Wavelet Packets”
• [0713] V. Zavadsky, “Multiresolution Approximations of Banach Spaces.”
• [0714] V. Zavadsky, “Wavelet Approximation of Sampled Functions.”
• [0715] B. G. Sherlock and D. M. Monro, “On the Space of Orthonormal Wavelets.”
• [0716] M. Vetterli and C. Herley, “Wavelets and Filter Banks: Theory and Design,” IEEE Transactions on Signal Processing, Vol. 40, 1992, pp. 2207-2232.
  Frame Decompositions
• [0717] J. Benedetto, C. Heil, and D. Walnut, “Differentiation and the Balian-Low Theorem.”
• [0718] O. Christensen and C. Heil, “Perturbations of Banach Frames and Atomic Decompositions.”
• [0719] D. M. Healy, Jr. and S. Li, “On Pseudo Frame Decompositions and Discrete Gabor Expansions.”
• [0720] S. Li, “General Frame Decompsotions, Pseudo-Duals and Applications for Weyl-Heisenberg Frames.”
• [0721] S. Li, “On Dimension Invariance of Discrete Gabor Expansions.”
  M-Band Wavelets and Filter Banks
• [0722] C. S. Burrus and R. A. Gopinath, “On the Correlation Structure of Multiplicity M Scaling Functions”
• [0723] C. S. Burrus and R. A. Gopinath, “Wavelets and Filter Banks”
• [0724] C. S. Burrus and R. A. Gopinath, “Unitary FIR Filter Banks and Symmetry”
• [0725] C. S. Burrus and R. A. Gopinath, “Theory of Modulated Filter Banks and Modulated Wavelet Tight Frames”
• [0726] C. S. Burrus and R. A. Gopinath, “Factorization Approach to Time-Varying Unitary Filter Bank Trees and Wavelets”
• [0727] C. Herley, “Boundary Filters for Finite-Length Signals and Time-Varying Filter Banks.”
• [0728] P. Steffen, P. Heller, R. A. Gopinath and C. S. Burrus, “The Theory of Regular M-Band Wavelets”
  Wavelets and General Signal Processing
• [0729] M. Vetterli and J. Kovacevic, “Wavelets and Subband Coding”, Prentice Hall, 1995.
• [0730] D. E. Ashpis and J. Lewalle, “Transport in bypass transition: mapping the active time scales using wavelet techniques”
• [0731] D. E. Ashpis and J. Lewalle, “Demonstration of wavelet techniques in the spectral analysis of bypass transition data”
• [0732] C. Basdevant, V. Perrier and T. Philipovitch, “Wavelet Spectra Compared to Fourier Spectra.”
• [0733] J. P. Bonnet, J. Lewalle and M. N. Glauser, “Coherent Structures: Past, Present and Future.”
• [0734] G. Buresti, J. Lewalle and P. Petagna, “Wavelet statistics and the near-field structure of coaxial jets”
• [0735] C. S. Burrus and R. A. Gopinath, “Wavelet-Based Lowpass/Bandpass Interpolation”
• [0736] C. S. Burrus, R. A. Gopinath and J. E. Odegard, “Design of Linear Phase Cosine Modulated Filter Banks for Subband Image Compression”
• [0737] S. Cabrera, V. Krienovich and O. Sirisaengtaksin, “Wavelets Compress Better Than All Other Methods: A 1-D Theorem.”
• [0738] S. Cabrera, V. Krienovich and O. Sirisaengtaksin, “Wavelet Nerual Networks are Optimal Approximators for Functions of One Variable.”
• [0739] R. Carmona, W. L. Hwang and B. Torresani, “Characterization of Signals by the Ridges of Their Wavelet Transforms.”
• [0740] R. Carmona, W. L. Hwang and B. Torresani, “Multi-Ridge Detection and Time-Frequency Reconstruction.”
• [0741] R. Coifman, “Adapted Multiresolution Analysis, Computation, Signal Processing and Operator Theory”
• [0742] R. Coifman, Y. Meyer, S. Quake and M. Wickerhauser, “Signal Processing and Compression with Wave Packets.”
• [0743] R. Coifman, Y. Meyer and M. V. Wickerhauser, “Wavelet Analysis and Signal Processing”
• [0744] P. Crane, H. Higuchi and J. Lewalle, “On the structure of two-dimensional wakes behind a pair of flat plates”
• [0745] M. Goldburg, “Applications of Wavelets to Quantization and Random Process Representations.” About 1.1 MB.
• [0746] D. M. Healy, Jr., J. Lu and J. B. Weaver, “Signal Recovery and Wavelet Reproducing Kernels.”
• [0747] D. M. Healy, Jr., J. Lu, J. B. Weaver and Y. Xu, “Noise Reduction With Multiscale Edge Representation and Perceptual Criteria.”
• [0748] D. M. Healy, Jr. and J. Lu, “Contrast Enhancement via Multiscale Gradient Transformations.”
• [0749] W. Hwang and S. Mallat, “Singularity Detection and Processing with Wavelets.”
• [0750] B Jawerth, Y. Liu and W. Sweldens, “Signal Compression with Smooth Local Trigonometric Bases.” An abstract is also available.
• [0751] M. M. Lankhorst and M. D. van der Laan, “Wavelet-Based Signal Approximation with Genetic Algorithms.”
• [0752] J. Lewalle, K. Read and M. T. Schobeiri, “Effect of unsteady wake-passing frequency on boundary layer transition—experimental investigation and wavelet analysis”
• [0753] J. Lewalle, S. J. Murphy and F. W. Peek, “Wavelet analysis of olfactory nerve response to stimulus”
• [0754] J. Lewalle, “Wavelet analysis of experimental data: some methods and the underlying physics”
• [0755] G. Strang, “Eigenvalues of (!2)H and convergence of the cascade algorithm.”
• [0756] G. Strang, “Creating and comparing wavelets.”
• [0757] A. R. Tate, “Pattern Recognition Analysis of in vivo Magnetic Resonance Spectra”
• [0758] D. Donoho, “Nonlinear Wavelet Methods for Recovery of Signals, Densities, and Spectra from Indirect and Noisy Data,” Different Perspectives on Wavelets, Proceeding of Symposia in Applied Mathematics, Vol 47, 1. Daubechies ed. Amer. Math. Soc., Providence, R.I., 1993, pp. 173 -205.
  Wavelets and Image Processing
• [0759] E. Adelson and E. Simoncelli, “Subband Image Coding with Three-tap Pyramids.”
• [0760] E. H. Adelson, W. T. Freeman, D. J. Heeger and E. P. Simoncelli, “Shiftable Multi-Scale Transforms.”
• [0761] E. H. Adelson and E. P. Simoncelli, “Subband Transforms.”
• [0762] V. R. Algazi, R. R. Estes and J. Lu, “Comparison of wavelet image coders using the Picture Quality Scale (PQS).”
• [0763] M. Bhatia, W. C. Karl, and A. S. Willsky, “A Wavelet-Based Method for Multiscale Tomographic Reconstruction.”
• [0764] M. Bhatia, W. C. Karl, and A. S. Willsky, “Using Natural Wavelet Bases and Multiscale Stochastic Models for Tomographic Reconstruction.”
• [0765] M. Louys, J. L. Starck, S. Mei, F. Bonnarel, and F. Murtagh, “Astronomical Image Compression.”
• [0766] M. Louys, J. L. Starck and F. Murtagh, “Lossless Compression of Astronomical Images.”
• [0767] F. Murtagh and J. L. Starck, “Wavelets and Multiscale Transforms in Massive Data Sets.”
• [0768] F. Murtagh and J. L. Starck, “Image Processing through Multiscale Analysis and Measurement Noise Modeling.”
• [0769] J. L. Starck and F. Murtagh, “Multiscale Entropy Filtering.”
• [0770] J. L. Starck and F. Murtagh, “Image Filtering by Combining Multiple Vision Models”.
• [0771] F. Murtagh, “Wedding the Wavelet Transform and Multivariate Data Analysis.”
• [0772] F. Murtagh and J. L. Starck, “Pattern Clustering based on Noise Modeling in Wavelet Space.”
• [0773] G. Zheng, J. L. Starck, J. G. Campbell and F. Murtagh, “Multiscale Transforms for Filtering Financial Data Streams.”
• [0774] M. Morehart, F. Murtagh and J. L. Starck, “Multiresolution Spatial Analysis.”
• [0775] F. Murtagh, J. L. Starck and M. W. Berry, “Overcoming the Curse of Dimensionality in Clustering by means of the Wavelet Transform.”
• [0776] R. A. Carmona, R. D. Frostig and W. L. Hwang, “Wavelet Analysis for Brain Function Imaging.”
• [0777] A. Chambolle, R. A. DeVore, N. Lee, and B. J. Lucier, “Nonlinear Wavelet Image Processing: Variational Problems, Compression, and Noise Removal through Wavelet Shrinkage.”
• [0778] H. Chao and P. Fisher, “An Approach of Fast Integer Reversible Wavelet Transforms for Image Compression.”
• [0779] R. A. DeVore and B. J. Lucier, “Fast Wavelet Techniques for Near-Optimal Image Processing”
• [0780] B. Deng, B. D. Jawerth, G. Peters and W. Sweldens, “Wavelet Probing for Compression Based Segmentation”. An abstract is also available.
• [0781] J. Fan and A. Laine, “An Adaptive Approach for Texture Segmentation by Multi-Channel Wavelet Frames.”
• [0782] W. T. Freeman and E. P. Simoncelli, “The Steerable Pyramid: A Flexible Architecture for Multi-Scale Derivative Computation.”/C Source Code (75 k)
• [0783] A. Grzeszczak, M. K. Mandal, S. Panchanathan and T. Yeap, “VLSI Implementation of Discrete Wavelet Transform.”
• [0784] O. Guleryuz, M. T. Orchard and Z. Xiong, “A DCT-based Embedded Image Coder.”
• [0785] D. M. Healy, Jr., J. Lu and J. B. Weaver, “Contrast Enhancement of Medical Images Using Multiscale Edge Representation.”
• [0786] C. Heil, P. N. Heller, G. Strang, V. Strela, and P. Topiwala, “Accuracy of Lattice Translates of Several Multidimensional Refinable Functions.”
• [0787] C. Herley, M. T. Orchard, K. Ramchandran and Z. Xiong, “Flexible Tree-structured Signal Expansions for Compression Using Time-Varying Filter Banks.”
• [0788] M. L. Hilton, B. D. Jawerth and A. Sengupta, “Compressing Still and Moving Images with Wavelets” with figure.
• [0789] P. Kovesi, “Image Features from Phase Congruency”
• [0790] B. Lin, “Wavelet Phase Filter for Denoising Tomographic Image Reconstruction”
• [0791] M. K. Mandal, T. Aboulnasr and S. Panchanathan, “Image Indexing Using Moments and Wavelets.”
• [0792] M. K. Mandal, E. Chan, X. Wang and S. Panchanathan, “Multiresolution Motion Estimation Techniques for Video Compression.”
• [0793] M. K. Mandal, S. Panchanathan and T. Aboulnasr, “Choice of Wavelets for Image Compression.”
• [0794] D. M. Monro and B. G. Sherlock, “Psychovisually Tuned Wavelet Fingerprint Compression”.
• [0795] D. M. Monro and B. G. Sherlock, “Optimised Wavelets for Fingerprint Compression”.
• [0796] P. Moulin, “A Multiscale Relaxation Algorithm for SNR Maximization in 2-D Nonorthogonal Subband Coding.”
• [0797] M. T. Orchard, Z. Xiong and Y. Zhang, “A Simple Deblocking Algorithm for JPEG Compressed Images Using Overcomplete Wavelet Representations.”
• [0798] M. T. Orchard, K. Ramchandran and Z. Xiong, “Wavelet Packets Image Coding Using Space-Frequency Quantization.”
• [0799] M. T. Orchard, K. Ramchandran and Z. Xiong, “Space-frequency Quantization for Wavelet Image Coding.”
• [0800] H. Pan, “Uniform Full-Information Image Matching Using Complex Conjugate Wavelet Pyramids”, with figures.
• [0801] H. Pan, “General Stereo Image Matching Using Symmetric Complex Wavelets,” presented at SPIE Conference: Wavelet Applications in Signal and Image Processing, VI. Denver, August 1996, Published in SPIE Proceedings, vol. 2825.
• [0802] P. Schröder and W. Sweldens, “Spherical wavelets: Efficiently representing functions on the sphere.” An abstract is also available.
• [0803] P. Schröder and W. Sweldens, “Spherical Wavelets: Texture Processing.” An abstract is also available.
• [0804] J. A. Solomon, J. Villasenor, A. B. Watson and G. Y. Yang, “Visual Thresholds For Wavelet Quantization Error.”
• [0805] V. Strela, P. Heller, G. Strang, P. Topiwala and C. Heil, “The application of multiwavelet filter banks to signal and image processing.”
• [0806] Y. Wang, “Image representations using multiscale differential operators.”
• [0807] Y. Wang and S. L. Lee, “Scale-space derived from B-splines.”
• [0808] G. Weiss, “Time-Frequency and Time-Scaling Methods in Signal and Image Processing”
• [0809] M. Wickerhauser, “Picture Compression by Best-Basis Subband Coding.”
• [0810] M. V. Wickerhauser, “High-Resolution Still Picture Compression”
• [0811] Z. Xiong, “Representation and Coding of Images Using Wavelets.”
• [0812] D. M. Monro and B. G. Sherlock, “Space-Frequency Balance in Biorthogonal Wavelets.”
• [0813] Xuejun Li, “Low Bit Rate Wavelet Image and Video Coding Algorithm and Software.”
  The FBI Wavelet Fingerprint Compression Standard
• [0814] J. N. Bradley and C. M. Brislawn, “Proposed First-Generation WSQ Bit Allocation Procedure”
• [0815] J. N. Bradley and C. M. Brislawn, “The Wavelet/Scalar Quantization Compression Standard for Digital Fingerprint Images.”
• [0816] J. Bradley, C. Brislawn and T. Hopper, “WSQ Gray-Scale Fingerprint Image Compression Specification.”
• [0817] J. Bradley, C. Brislawn and T. Hopper, “The FBI Wavelet/Scalar Quantization Standard for Gray-Scale Fingerprint Image Compression” with figures.
• [0818] C. M. Brislawn, Classification of Nonexpansive Symmetric Extension Transforms for Multirate Filter Banks”
• [0819] C. M. Brislawn, “Fingerprints Go Digital”
• [0820] C. M. Brislawn, “Preservation of Subband Symmetry in Multirate Signal Coding.”“The FBI Wavelet/Scalar Quantization Fingerprint Image Compression Standard.”
  Wavelets and Speech Processing
• [0821] E. Wesfreid and M. V. Wickerhauser, “Adapted Local Trigonometric Transforms and Speech Processing”
• [0822] M. Wickerhauser, “Acoustic Signal Compression with Wavelets Packets.”
  Wavelets and Ordinary Differential Equations
• [0823] G. Beylkin, “On Wavelet-based Algorithms for Solving Differential Equations.”
• [0824] B Jawerth and W. Sweldens, “Wavelet Multiresolution Analyses Adapted for the Fast Solution of Boundary Value Ordinary Differential Equations.” An abstract is also available.
• [0825] P. Monasse and V. Perrier, “Ondelettes sur l'Intervalle pour la Prise en Compte de Conditions aux Limites.”
• [0826] A. Rieder, “Semi-Algebraic Multi-level Methods Based on Wavelet Decompositions I: Application to Two-Point Boundary Problems”
• [0827] W. C. Shann and J. C. Xu, “Galerkin-wavelet Methods for Two Point Boundary Value Problems.”
  Wavelets and Partial Differential Equations
• [0828] G. Kaiser, “Complex-Distance Potential Theory and Hyperbolic Equations”
• [0829] A. Averbuch, G. Beylkin R. R. Coifman and M. Israeli, “Multiscale Inversion of Elliptic Operators.”
• [0830] E. Bacry, S. Mallat and G. Papanicolaou, “A Wavelet Based Space-Time Adaptive Numerical Method for Partial Differential Equations”
• [0831] G. Beylkin and N. Coult, “A Multiresolution Strategy for Reduction of Elliptic PDE's and Eigenvalue Problems.”
• [0832] G. Beylkin and J. H. Keiser, “On the Adaptive Numerical Solution of Nonlinear Partial Differential Equations in Wavelet Bases.”
• [0833] D. M. Bond and S. A. Vavasis, “Fast Wavelet Transforms for Matrices Arising From Boundary Element Methods.”
• [0834] T. Chan, W. Tang and W. Wan,.
• [0835] P. Charton and V. Perrier, “Factorisation sur Bases d'Ondelettes du Noyeau de la Chaleur et Algorithmes Matriciels Rapides Associes.”
• [0836] P. Charton and V. Perrier, “Towards a Wavelet Based Numerical Scheme for the Two-Dimensional Navier-Stokes Equations.”
• [0837] P. Charton and V. Perrier, “A Pseudo-Wavelet Scheme for the Two-Dimensional Navier-Stokes Equations.”
• [0838] S. Dahlke and A. Kunoth, “Biorthogonal Wavelets and Multigrid.”
• [0839] S. Dahlke and I. Weinreich, “Wavelet-Galerkin Methods: An Adapted Biorthogonal Wavelet Basis.”
• [0840] S. Dahlke and I. Weinreich, “Wavelet Bases Adapted to Pseudo-Differential Operators.”
• [0841] W. Dahmen and A. Kunoth, “Multilevel Preconditioning.”
• [0842] W. Dahmen, A. Kunoth and K. Urban “A Wavelet-Galerkin Method for the Stokes-Equations,” also full version with pictures.
• [0843] R. Glowinski, T. Pan, R. O. Wells, Jr. and X. Zhou, “Wavelet and Finite Element Solutions for the Neumann Problem Using Fictitious Domains”
• [0844] R. Glowinski, A. Rieder, R. O. Wells, Jr. and X. Zhou, “A Wavelet Multigrid Preconditioner for Dirichlet Boundary Value Problems in General Domains.”
• [0845] R. Glowinski, A. Rieder, R. O. Wells, Jr. and X. Zhou, “A Preconditioned CG-Method for Wavelet-Galerkin Discretizations of Elliptic Problems”
• [0846] F. Heurtaux, F. Planchon and M. V. Wickerhauser, “Scale Decomposition in Burgers' Equation”
• [0847] A. Jiang,.
• [0848] J. H. Keiser, “On I. Wavelet Based Approach to Numerical Solution on Nonlinear Partial Differential Equations and II. Nonlinear Waves in Fully Discrete Dynamical Systems.”
• [0849] A. Kunoth, “Multilevel Preconditioning—Appending Boundary Conditions by Lagrange Multipliers.”
• [0850] G. Leaf and J. M. Restrepo, “Wavelet-Galerkin Discretization of Hyperbolic Equations.”
• [0851] J. Lewalle, “Wavelet Transforms of some Equations of Fluid Mechanics”
• [0852] J. Lewalle, “Energy Dissipation in the Wavelet-Transformed Navier-Stokes Equations”
• [0853] J. Lewalle, “On the effect of boundary conditions on the multifractal statistics of incompressible turbulence”
• [0854] J. Lewalle, “Diffusion is Hamiltonian”.
• [0855] D. Lu, T. Ohyoshi and L. Zhu, “Treatment of Boundary Conditions in the Application of Wavelet-Galerkin Method to a SH Wave Problem”
• [0856] P. Monasse and V. Perrier, “Orthonormal Wavelet Bases Adapted for Partial Differential Equations with Boundary Conditions.”
• [0857] A. Rieder and X. Zhou, “On the Robustness of the Damped V-Cycle of the Wavelet Frequency Decompositions Multigrid Method”
• [0858] A. Rieder, R. O. Wells, Jr. and X. Zhou, “A Wavelet Approach to Robust Multilevel Solvers for Anisotropic Elliptic Problems.”
• [0859] A. Rieder, R. O. Wells, Jr. and X. Zhou, “On the Wavelet Frequency Decomposition Method”
• [0860] K. Urban, “A Wavelet-Galerkin Algorithm for the Driven-Cavity-Stokes-Problem in Two Space Dimensions.”
• [0861] O. V. Vasilyev and S. Paolucci, “A Dynamically Adaptive Multilevel Wavelet Collocation Method for Solving Partial Differential Equations in a Finite Domain.”
• [0862] O. V. Vasilyev and S. Paolucci, “Thermoacoustic Wave Propagation Modeling Using a Dynamically Adaptive Wavelet Collocation Method.”
• [0863] O. V. Vasilyev and S. Paolucci, “A Fast Adaptive Wavelet Collocation Algorithm for Multi-Dimensional PDEs.” with figures.
• [0864] O. V. Vasilyev, S. Paolucci and M. Sen, “A Multilevel Wavelet Collocation Method for Solving Partial Differential Equations in a Finite Domain.”
• [0865] O. V. Vasilyev, Y. Y. Podladchikov and D. A. Yuen, “Modeling of Compaction Driven Flow in Poro-Viscoelastic Medium Using Adaptive Wavelet Collocation Method.” with figures.
• [0866] O. V. Vasilyev, D. A. Yuen and S. Paolucci, “The Solution of PDEs Using Wavelets.” with figures.
• [0867] O. V. Vasilyev, D. A. Yuen and Y. Y. Podladchikov, “Applicability of Wavelet Algorithm for Geophysical Viscoelastic Flow.” with figures.
• [0868] R. O. Wells, Jr. and X. Zhou, “Wavelet Solutions for the Dirichlet Problem”
• [0869] R. O. Wells, Jr. and X. Zhou, “Wavelet Interpolation and Approximate Solution of Elliptic Partial Differential Equations”
• [0870] R. O. Wells, Jr. and X. Zhou, “Representing the Geometry of Domains by Wavelets with Applications to Partial Differential Equations”
• [0871] R. O. Wells, Jr., “Multiscale Applications of Wavelets to Solutions of Partial Differential Equations”
  Wavelets and Numerical Analysis
• [0872] G. Beylkin, R. Coifman and V. Rokhlin, “Fast Wavelet Transforms and Numerical Algorithms I.”
• [0873] G. Beylkin, “On the Representation of Operators in Bases of Compactly Supported Wavelets.”
• [0874] G. Beylkin, “On the Fast Algorithm for Multiplication of Functions in the Wavelet Bases.”
• [0875] G. Beylkin, “Wavelets and Fast Numerical Algorithms.” Lecture notes for an AMS short course, 1993.
• [0876] G. Beylkin, “Wavelets, Multiresolution Analysis and Fast Numerical Algorithms.” Draft of INRIA lectures, May 1991.
• [0877] G. Beylkin and M. E. Brewster, “A Multiresolution Strategy for Numerical Homogenization.”
• [0878] P. Charton and V. Perrier, “Produits Rapides Matrices-Vecteur en Bases d'Ondelettes: Application a la Resolution Numerique d'Equation aux Derivees Partielles.”
• [0879] P. Charton, “Produits de Matrices Rapides en Bases d'Ondelettes: Application a la Resolution Numerique d'Equation aux Derivees Partielles.”
• [0880] N. H. Getz, “A Fast Discrete Periodic Wavelet Transform.” An associated toolbox of Matlab routines is also available.
• [0881] L. Jameson, “On the Spline-Based Wavelet Differentiation Matrix.”
• [0882] L. Jameson, “On the Differention Matrix for Daubechies-Based Wavelets on an Interval.”
• [0883] L. Jameson, “On the Daubechies-Based Wavelet Differentiation Matrix.”
• [0884] L. Jameson, “On the Wavelet Optimized Finite Difference Method.”
• [0885] E. Kolaczyk, “Wavelet Methods for the Inversion of Certain Homogeneous Linear Operators in the Presence of Noisy Data,” with FIG. 5.1, FIGS. 5.2, FIG. 5.4, FIG. 5.5, FIGS. 5.6, FIGS. 5.8, FIG. 5.10, FIGS. 5.11, FIG. 5.13, and FIGS. 5.14.
• [0886] R. Piessens and W. Sweldens, “Quadrature Formulae and Asymptotic Error Expansion of Wavelet Approximations of Smooth Functions.” An abstract is also available.
• [0887] R. Piessens and W. Sweldens, “Asymptotic Error Expansion of Wavelet Approximations of Smooth Functions II.” An abstract is also available.
• [0888] W. C. Shann, “Quadratures Involving Polynomials and Daubechies' Wavelets.”
• [0889] W. Sweldens, “Construction and Application of Wavelets in Numerical Analysis.”
• [0890] M. Wickerhauser, “Nonstandard Matrix Multiplication.”
• [0891] M. V. Wickerhauser, “Computation with Adapted Time-Frequency Atoms”
• [0892] M. V. Wickerhauser, “Wavelet Approximations to Jacobians and the Inversion of Complicated Maps”
  Wavelets and Statistics
• [0893] F. Abramovich, T. Sapatinas and B. W. Silverman, “Wavelet Thresholding via a Bayesian Approach.”
• [0894] F. Abramovich, T. Sapatinas and B. W. Silverman, “Stochastic Atomic Decompositions in a Wavelet Dictionary.”
• [0895] F. Abramovich and B. W. Silverman, “The Vaguelette-Wavelet Decomposition Approach to Statistical Inverse Problems.”
• [0896] E. H. Adelson and E. P. Simoncelli, “Noise Removal via Bayesian Wavelet Coring.”
• [0897] A. Antoniadis, G. Gregoire and G. P. Nason, “Density and Hazard Rate Estimation for Right Censored Data using Wavelet Methods.”
• [0898] T. Bailey, T. Sapatinas, K. Powell and W. J. Krzanowski, “Signal Detection in Underwater Sounds using Wavelets.”
• [0899] A. G. Bruce, D. L. Donoho, H. Gao and R. D. Martin, “Denoising and Robust Non-linear Wavelet Analysis.”
• [0900] A. G. Bruce and H. Gao, “WaveShrink: Shrinkage Functions and Thresholds.”
• [0901] A. G. Bruce and H. Gao, “WaveShrink with Semisoft Shrinkage.”
• [0902] A. G. Bruce and H. Gao, “Understanding WaveShrink: Variance and Bias Estimation.”
• [0903] A. G. Bruce, H. Gao and D. Ragozin, “S+WAVELETS: An Object-Oriented Toolkit for Wavelet Analysis.”
• [0904] A. G. Bruce and H. Gao, “S+WAVELETS: Algorithms and Technical Details.”
• [0905] J. Buckheit and D. Donoho, “WaveLab and Reproducible Research.”
• [0906] J. F. Burn, A. M. Wilson and G. P. Nason, “Impact During Equine Locomotion: Techniques for Measurement and Analysis.”
• [0907] R. Coifman and N. Saito, “Local Discriminant Bases.”
• [0908] R. Coifman and F. Majid, “Adapted Waveform Analysis and Denoising.”
• [0909] R. Coifman and D. Donoho, “Translation-Invariant De-Noising.”
• [0910] R. Dahlhaus, M. H. Neumann and R. von Sachs, “Non-linear Wavelet Estimation of Time—Varying Autoregressive Processes.”
• [0911] A. Davis, A. Marshak and W. Wiscombe, “Wavelet-Based Multifractal Analysis of Non-Stationary and/or Intermittent Geophysical Signals.” with figures.
• [0912] B. Deylon and A. Juditsky, “Wavelet Estimators. Global Error Mesures Revisited.”
• [0913] D. Donoho, “Nonlinear Solution of Linear Inverse Problems by Wavelet-Vaguelette Decomposition”
• [0914] D. Donoho, “Smooth Wavelet Decompositions with Blocky Coefficient Kernels”
• [0915] D. Donoho, “De-noising by Soft Thresholding”
• [0916] D. Donoho, “Interpolating Wavelet Transforms”
• [0917] D. Donoho, “Unconditional Bases are Optimal Bases for Data Compression and for Statistical Estimation”
• [0918] D. Donoho and I. Johnstone, “Adapting to Unknown Smoothness by Wavelet Shrinkage”
• [0919] D. Donoho and I. Johnstone, “Ideal Spatial Adaptation via Wavelet Shrinkage”
• [0920] D. Donoho and I. Johnstone, “Minimax Estimation via Wavelet Shrinkage”
• [0921] D. Donoho and I. Johnstone, “Minimax Risk over l_p Balls”
• [0922] D. Donoho, I. Johnstone, G. Kerkyacharian and D. Picard, “Density Estimation via Wavelet Shrinkage”
• [0923] D. Donoho, I. Johnstone, G. Kerkyacharian and D. Picard, “Wavelet Shrinkage: Asymptopia?”
• [0924] D. Donoho and I. Johnstone, “Ideal Denoising in an Orthonormal Basis Chosen From a Library of Bases.”
• [0925] D. Donoho, S. Mallat and R. von Sachs, “Estimating Covariances of Locally Stationary Processes: Rates of Convergence of Best Basis Methods.”
• [0926] T. Downie and B. W. Silverman, “The Discrete Multiple Wavelet Transform and Thresholding Methods.”
• [0927] H. Y. Gao, “Choice of Thresholds for Wavelet Shrinkage Estimate of the Spectrum.”
• [0928] P. Goel and B. Vidakovic, “Wavelet Transformations as Diversity Enhancers”
• [0929] P. Hall and G. P. Nason, “On Choosing a Non-integer Resolution Level when Using Wavelet Methods.”
• [0930] I. Johnstone, “Minimax Bayes, Asymptotic Minimax and Sparse Wavelet Priors”
• [0931] I. M. Johnstone and B. W. Silverman, “Wavelet Threshold Estimators for Data with Correlated Noise.”
• [0932] A. Juditsky, “Wavelet Estimators. Adapting To Unkown Smoothness.”
• [0933] A. Juditsky and F. Leblanc, “Computing Wavelet Density Estimators for Stochastic Processes.”
• [0934] G. Katul and B. Vidakovic, “Partitioning eddy motion using Lorentz wavelet filtering.”
• [0935] R. Morgan and G. P. Nason, “Wavelet Shrinkage of Itch Response Sata.”
• [0936] P. Moulin, “Wavelet Thresholding Techniques for Power Spectrum Estimation.”
• [0937] G. P. Nason and B. W. Silverman, “The Discrete Wavelet Transform in S.”
• [0938] G. P. Nason and B. W. Silverman, “The Stationary Wavelet Transform and some Statistical Applications.”
• [0939] G. P. Nason and B. W. Silverman, “Wavelets for Regression and other Statistical Problems.”
• [0940] G. P. Nason, T. Sapatinas and A. Sawczenko, “Statistical Modelling of Time Series using Non-decimated Wavelet Representations.”
• [0941] G. P. Nason, “Wavelet Regression by Cross-Validation”
• [0942] G. P. Nason, “Functional Projection Pursuit.”
• [0943] M. H. Neumann and R. von Sachs, “Wavelet Thresholding in Anisotropic Function Classes and Application to Adaptive Estimation of Evolutionary Spectra.”
• [0944] A. B. Owen, “Monte Carlo Variance of Scrambled Equidistribution Quadrature.”
• [0945] D. B. Percival, “On the Estimation of the Wavelet Variance.”
• [0946] A. Pinheiro and B. Vidakovic, “Estimating the Square Root of a Density Via Compactly Supported Wavelets.”
• [0947] J. Raz, L. Dickerson and B. Turetsky, “A Wavelet Packet Model of Evoked Potentials.”
• [0948] N. Saito, “Local Feature Extraction and Its Appplications Using a Library of Bases.”
• [0949] N. Saito, “Simultaneous Noise Supression and Signal Compression using a Library of Orthonormal Bases and the Minimum Description Length Criterion.”
• [0950] B. Vidakovic, “A Note on Random Densities via Wavelets”
• [0951] B. Vidakovic, “Nonlinear Wavelet Shrinkage with Bayes Rules and Bayes Factors.”
• [0952] R. von Sachs, G. P. Nason and G. Kroisandt, “Adaptive Estimation of the Evolutionary Wavelet Spectrum.”
• [0953] R. von Sachs and K. Schneider, “Smoothing of Evolutionary Spectra by Non-linear Thresholding.” Also available are the figures.
• [0954] R. von Sachs and M. H. Neumann, “A Wavelet-based Test for Stationarity.”
• [0955] R. von Sachs and B. MacGibbon, “Non-parametric Curve Estimation by Wavelet Thresholding with Locally Stationary Errors.”
• [0956] A. T. Walden, D. B. Percival and E. J. McCoy, “Spectrum Estimation by Wavelet Thresholding of Multitaper Estimators.”
• [0957] Yazhen Wang, “Jump and sharp cusp detection by wavelets.”
• [0958] Yazhen Wang, “Function estimation via wavelet shrinkage for long-memory data.”
• [0959] Yazhen Wang, “Small ball problems via wavelets for Gaussian processes.”
• [0960] Yazhen Wang, “Fractal function estimation via wavelet shrinkage.”
• [0961] Yazhen Wang, “Minimax estimation via wavelets for indirect long-memory data.”
• [0962] Yazhen Wang, “Change curve estimation via wavelets” (with an application to image processing); FIG. 4(a), FIG. 4(b).
• [0963] Yazhen Wang, “Change-point analysis via wavelets for indirect data.”
• [0964] Yazhen Wang, “Self-similarity index estimation via wavelets for locally self-similar processes”(with Cavanaugh and Song); FIG. 1, FIG. 2, FIGS. 3 and 4.
• [0965] M. V. Wickerhauser, “Fast Approximate Factor Analysis.”
  Wavelets and Econometrics
• [0966] S. A. Greenblatt, “Wavelets in Economics: An Application to Outlier Testing.”
• [0967] M. J. Jensen, “Wavelet Analysis of Fractionally Integrated Processes.”
• [0968] M. J. Jensen, “OLS Estimate of the Fractional Differencing Parameter Using Wavelets Derived From Smoothing Kernels.”
  Wavelets and Fractals
• [0969] A. Davis, A. Marshak and W. Wiscombe, “Wavelet-Based Multifractal Analysis of Non-Stationary and/or Intermittent Geophysical Signals.” with figures.
• [0970] C. Jones, 2-D Wavelet Packet Analysis of Structural Self-Organization and Morphogenic Regulation in Filamentous Fungal Colonies.
• [0971] J. Lewalle, “Wavelet Transforms of the Navier-Stokes Equations and the Generalized Dimensions of Turbulence”
• [0972] W. Hwang and S. Mallat, “Characterization of Self-Similar Multifractals with Wavelet Maxima.”
  Wavelets and Communication Theory
• [0973] J. Dill and A. R. Lindsey, “Wavelet Packet Modulation: A Generalized Method for Orthogonally Multiplexed Communication.”
• [0974] R. Learned, H. Krim, B. Claus, A. S. Willsky, and W. C. Karl, “Wavelet-Packet-Based Multiple Access Communication.”
• [0975] A. R. Lindsey, “Multidimensional Signaling via Wavelet Packets.”
• [0976] A. R. Lindsey, Generalized Orthogonally Multiplexed Communication via Wavelet Packet Bases, chapter 1, chapter 2, chapter 3, chapter 4, chapter 5, chapter 6. Also with appendix and references.
  Wavelets and Computer Graphics
• [0977] M. Cohen, S. Gortler, P. Hanrahan and P. Schröder, “Wavelet Radiosity.” With FIG. 12 and FIG. 14.
• [0978] M. Cohen, S. Gortler, P. Hanrahan and P. Schröder, “Wavelet Projections for Radiosity.”
• [0979] A. Dreger, M. H. Gross R. Koch and L. Lippert, “A New Method to Approximate the Volume Rendering Equation using Wavelet Bases and Piecewise Polynomials,” with FIGS. 5-6, FIGS. 7-10, and FIGS. 11-13. Also abstract available. Technical Report No. 220, Computer Science Department, ETH Zürich, 1994.
• [0980] A. Fournier, “Wavelets and their Applications in Computer Graphics.” This is 2.5 MB compressed.
• [0981] M. H. Gross and L. Lippert, “Fast Wavelet Based Volume Rendering by Accumulation of Tranparent Texture Maps.” With FIG. 6, FIG. 7, FIG. 8, FIG. 9, FIG. 10 and FIG. 11. Also abstract available. Technical Report No. 228, Computer Science Department, ETH Zürich, 1995.
• [0982] M. H. Gross and R. Koch, “Visualization of Multidimensional Shape and Texture Features in Laser Range Data using Complex-Valued Gabor Wavelets.”
• [0983] M. H. Gross and L. Lippert, “Ray-tracing of Multiresolution B-Spline Volumes.” Also abstract available. Technical Report No. 239, Computer Science Department, ETH Zürich, 1996.
• [0984] P. Hanrahan and P. Schröder, “Wavelet Methods for Radiance Computations.” With FIG. 8, FIG. 9 left, FIG. 9 right, FIG. 10, FIG. 10 top left and FIG. 10 top right.
• [0985] C. Herley, “Exact Interpolation and Iterative Subdivision Schemes.”
• [0986] P. Schröder, W. Sweldens and D. Zorin, “Interpolating Subdivision for Meshes with Arbitrary Topology”. An abstract is also available.
  Wavelets and Physics
• [0987] J. C. van den Berg, ed., “Wavelets in Physics”, Cambridge University Press, 1999 (a survey of many applications).
• [0988] G. Kaiser, “A Detailed Introduction to Mathematical and Physical Wavelets”
• [0989] C. Best and A. Schäfer, “Variational Description of Statistical Field Theories using Daubechies' Wavelets.”
• [0990] G. Beylkin, J. Dunn and D. Gines, “Order N Static and Quasi-Static Computations in Electrodynamics using Wavelets.”
• [0991] J. C. Cohen and T. Chen, “Fundamentals of the Discrete Wavelet Transform for Seismic Data Processing.”
• [0992] A. Fournier, “Wavelet Analysis of Observed Geopotential and Wind: Blocking and Local Energy Coupling Across Scales.”
• [0993] A. Fournier, “Wavelet Multiresolution Analysis of Numerically Simulated 3d Radiative Convection.”
• [0994] A. Fournier, “Wavelet Representation of Lower-Atmospheric Long Nonlinear Wave Dynamics, Governed by the Benjamin-Davis-Ono-Burgers Equation.”
• [0995] F. Herrmann, “A scaling medium representation, a discussion on well-logs, fractals and waves.”An abstract is also available.
• [0996] I. Pierce and L. Watkins, “Modelling optical pulse propagation in nonlinear media using wavelets.”
• [0997] W. C. Shann, “Finite Element Methods for Maxwell's Equations with Stationary Magnetic Fields and Galerkin-wavelet Methods for Two Point Boundary Value Problems,” with separate abstract and table of contents.
• [0998] L. R. Watkins and Y. R. Zhou, “Modelling Propagation in Optical Fibres using Wavelets.”
• [0999] R. O. Wells, “Adaptive Wave Propogation Modelling.”
• [1000] L. Zubair, “Studies in Turbulence using Wavelet Transforms for Data Compression and Scale-Separation.”
• [1001] A. Fournier, “An introduction to orthonormal wavelet analysis with shift invariance: Application to observed atmospheric-blocking spatial structure”, to appear in J. Atmos. Sci., Dec. 1, 2000.
• [1002] A. Fournier, “Atmospheric energetics in the wavelet domain I: Governing equations and interpretation for idealized flows”, submitted to J. Atmos. Sci., 2000 (revised).
• [1003] A. Fournier, “Atmospheric energetics in the wavelet domain II: Time-averaged observed atmospheric blocking”, submitted to J. Atmos. Sci., 1999.
• [1004] A. Fournier, “Atmospheric energetics in the wavelet domain III: Instantaneous transfers between block and local eddies”, submitted to J. Atmos. Sci., 1999.
  Hardware and Software Implementation of Wavelet Transforms
• [1005] J. Fridman and E. S. Manolakos, “On Linear Space-Time Mapping for the 1-D Discrete Wavelet Transform.”
• [1006] J. Fridman and E. S. Manolakos, “Distributed Memory and Control VLSI Architectures for the 1-D Discrete Wavelet Transform.”
• [1007] J. Lu, “Computation of 2-D Wavelet Transform on the Massively Parallel Computer for Image Processing.”
• [1008] MathSoft Engineering & Education, Inc, “Wavelets Extension Pack”, 1999.
• [1009] O. Nielsen and M. Hegland, “A Scalable Parallel 2D Wavelet Transform Algorithm.”

• [1010] GEB: Games and Economic Behavior
• [1011] EMA: Econometrica
• [1012] JET: Journal of Economic Theory
• [1013] IJGT: International Journal of Game Theory
• [1014] AER: American Economic Review
• [1015] QJE: Quarterly Journal of Economics
• [1016] JPE: Journal of Political Economy
• [1017] REStud: Review of Economic Studies
  Description of Games
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  Rationality, Dominance, Weak Dominance etc
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• [1026] Larry Samuelson, Dominated strategies and common knowledge. GEB 1992
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  Equilibrium: Nash, Refinements, Correlated
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  The Extensive Form Games with Perfect Information
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• [1037] Aumann Backward induction and common knowledge of rationality. GEB 1995
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  Hyperbolic Discounting
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  The Economics of Altruism
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• [1044] Bernheim and Stark, Altruism within the family reconsidered: do nice guys finish last. AER 1988
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• [1046] Bruce and Waldman, Transfers in kind: why they can be efficient and non-paternalistic. AER 1991
• [1047] Jack Robles, Paternal altruism or smart parent altruism? CU WP 98-10
• [1048] Mathew Rabin, Incorperating fairness into economics and game theory. AER 1993
• [1049] Ray and Ueda, Egalitarianism and incentives. JET 1996
• [1050] Bernheim, Shleifer adn Summers, The strategic bequest motive. JPE 1985
  Extensive Form Games without Perfect Information
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• [1052] Van Damme, Stable Equilibria and forward induction. JET 1989.
  Strategic Information Transmision
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• [1054] Cho and Kreps, Signalling games and stable equilibria. QJE 1987
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• [1056] Milgrom and Roberts, Limit pricing and entry under incomplete information: an equilibrium analysis. EMA 1982 (pages 443-459)
• [1057] Cho and Sobel, Strategic Stability and uniqueness in signalling games. JET 1990.
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  Folk Theorems for Repeated Games
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• [1062] Benoit and Krishna. Finitely Repeated games. Econometrica, 1985.
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  Renegotiation
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• [1070] Andreas Blume, Interplay communication in repeated games. GEB 1994
• [1071] Geir Asheim, Extending renegotiation proofness to infinite horizon games. GEB 1991
• [1072] Bernheim and Ray, Collective dynamic consistency in repeated games. GEB 1989
• [1073] Farrel and Maskin, Renegotiation in Repeated Games. GEB 1989
  Cooperative Game Theory
• [1074] Freidman, Game theory with applications to economics chapter 6 and 7
• [1075] Nash, The Bargaining problem. EMA 1950
• [1076] Kalai and Smordinski, Other Solutions to Nash's problem. EMA 1975
  Noncooperative Bargaining
• [1077] Rubinstein, Perfect equiibrium in a bargaining model. EMA 1982
• [1078] Joel Watson, Alternating offer bargaining with two sided incomplete information. REStud 1999
  Reputation
• [1079] Kreps, Milgrom, Roberts and Wilson, Reputation and imperfect information: predation, reputation and entry deterence: rational cooperation in the finitely repeated prisoner's dilemna. JET 1981
• [1080] Aumann and Sorin, Cooperation and Bounded recal. GEB 1989
• [1081] Klaus Schmidt, Reputation and equilibrium characterization in repeated games with conflicting interests, Econometrica 1993, 325-352
• [1082] Cripps and Thomas, Reputation and Commitment in Two person games without discounting, EMA, 1995, 1401-1420
• [1083] Joel Watson, A reputation refinement withough equilibrium, EMA 1993, 199-206
• [1084] Celentani, Fudenberg and Levine, Maintaining a reputation against a long lived opponent EMA 1996, 691-704
  Evolutionary Game Theory
• [1085] Vince Crawford, An Evolutionary interpretation of VHBB's experimental results on coordination. GEB 1991
• [1086] Gilboa and Matsui, Social Stability and Equilibrium, EMA 1991
• [1087] Kandori, Mailath and Rob, Learning, Mutation, and Long Run Equilibria in games, EMA 1993.
• [1088] Peyton Young, An Evolutionary Model of Bargaining, JET 1993
• [1089] Peyton Young, The Evolution of Conventions, EMA 1993
• [1090] Larry Samuelson, Stochastic Stability with alternative best replies. JET
• [1091] Noldeke and Samuelson, The Evolution of Backwards and Forwards Induction, GEB 1993
• [1092] Jack Robles, An Evolutionary Folk Theorem For Finitely Repeated Games CU WP 99—
• [1093] Kim and Sobel, An Evolutionary Approach to Preplay Communication EMA 1995
  General Game Theory
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• [1095] Dixit A., & Nalebuff B., Thinking Strategically: the Competitive Edge in Business, Politics, and Everyday Life, New York: Norton, 1991.
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• [1099] Ghemawat P., Games Businesses Play: Cases and Models, New York: Wiley, 1995.
• [1100] Gardner R., Games for Business and Economics, New York: Wiley, 1995.
  Strategic Decision Making
• [1101] Dixit & Nalebuff, Intro; Ch2 Anticipating your rival's response;
• [1102] Ch3 Seeing through your rival's response.
• [1103] Barnett, F. W. Making game theory work in practice, Wall Street Journal, 1995.
• [1104] Bierman & Fernandez, Ch5 Nash equilibrium I, Ch11 Nash equilibrium II
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• [1108] McMillan J., Ch3 Understanding cooperation and conflict.
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• [1110] Baird, Gertner, & Picker, Ch1 Simultaneous decision-making and the normal form game.
• [1111] Gardner, Ch1 Introduction, Ch2 Two-person games, Ch16 Voting games.
• [1112] Rasmusen, Ch1 The rules of the game.
• [1113] Schelling T. C., What is game theory? in his Choice and Consequence: Perspectives of an Errant Economist, Camb.: Harvard UP, 1980.
  Decision Analysis—Games Against Nature
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  Strategic Moves
• [1120] Dixit & Nalebuff, Ch5 Strategic moves.
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• [1122] Gardner, Ch4 n-person games, Ch5 Non-cooperative games.
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  Credible Commitment
• [1126] Dixit & Nalebuff, Ch6 Credible commitments.
• [1127] Bierman & Fernandez, Ch23 Subgame-perfect equilibrium
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• [1129] Gardner, Ch6 Credibility and subgame perfection.
• [1130] Ghemawat, Ch3 Preemptive capacity expansion in the titanium dioxide industry.
  Repetition and Reputation
• [1131] Dixit & Nalebuff, Ch4 Resolving the Prisoner's Dilemma; Ch9 Cooperation and coordination.
• [1132] Nowak, M., R. May, & K. Sigmund, The arithmetic of mutual help, Scientific American, 1995
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• [1135] Baird Gertner & Picker, Ch2 Dynamic interaction and the extensive-form game, Ch5 Reputation and repeated games.
• [1136] Gardner, Ch7 Repeated games, Ch8 Evolutionary stability and bounded rationality.
• [1137] Rasmusen, Ch4 Dynamic games and symmetric information, Ch5 Reputation and repeated games with symmetric information.
  Unpredictability
• [1138] Dixit & Nalebuff, Ch7 Unpredictability; Ch8 Brinkmanship.
• [1139] Bierman & Fernandez, Ch11.9
• [1140] Gardner, Ch3 Mixed strategies.
• [1141] Rasmusen, Ch3 Mixed and continuous strategies.
  Bargaining
• [1142] Dixit & Nalebuff, Ch10 The voting strategy; Ch11 Bargaining.
• [1143] McMillan, Ch5 Gaining bargaining power; Ch6 Using information strategically.
• [1144] Elster J., Ch14 Bargaining, in Nuts and Bolts for the Social Sciences, Camb.: CUP, 1989
• [1145] Murnighan J. K., Game's End, Chapter 15 in his: Bargaining Games: A New Approach to Strategic Thinking in Negotiations, NY: William Morrow, 1992.
• [1146] Bierman & Fernandez, Ch6 Bargaining.
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• [1148] Baird Gertner & Picker, Ch7 Noncooperative bargaining
• [1149] Gardner, Ch12 Two-person bargains. Ch14 n-person bargaining and the core.
• [1150] Rasmusen, Ch11 Bargaining.
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  Using Information Strategically
• [1152] McMillan, Ch6 Using information strategically
• [1153] Bierman & Fernandez, Ch17 Bayesian equilibrium, Ch19 Adverse selection and credit rationing
• [1154] Rasmusen, Ch2 Information P-13
• [1155] Baird Gertner & Picker, Ch4 Signalling, screening, and nonverifiable information
• [1156] Gardner, Ch9 Signaling games.
  Bidding in Competition
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• [1170] Rasmusen, Ch12 Auctions.
  Contracting, or the Rules of the Game
• [1171] Kay, Ch4 Relationships and contracts.
• [1172] Dixit & Nalebuff, Ch12 Incentives.
• [1173] McMillan, Ch8 Creating incentives; Ch9 Designing contracts; Ch10 Setting executives' salaries.
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  Choosing the Right Game: Co-opetition
• [1178] Brandenburger A. M. & B. J. Nalebuff, The right game: using Game Theory to shape strategy, Harvard Business Review, 1995
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[1333] Simulating large ad-hoc networks with ns-2 V. Naoumov, http://www.terminodes.org/MV2003-Present/Lu13/Simulating-Naoumov.pdf

[1334] Security of emergent properties in ad-hoc networks Prof. V. Gligor, Univ. of Maryland www.terminodes.org/MV2003-Present/Ma14/Gligor-MonteVerita.pdf

[1335] On the self-organization of security in multi-hop networks Prof. J P. Hubaux www.terminodes.org/MV2003-Present/Ma14/Multi-Hop-JPH.pdf

[1336] Immune Networking Systems Prof. J.-Y. Le Boudec www.terminodes.org/MV2003-Present/Ma14/ImmuneLeBoudec.pdf

[1337] Fair exchange with guardian angels G. Avoine www.terminodes.org/MV2003-Present/Ma14/FairExchange-Avoine.pdf

[1338] Spatial analysis of mobile ad-hoc networks under the Signal to Interference Ratio connectivity model Prof. F. Baccelli, Ecole Normale Supérieure and INRIA, Paris www.terminodes.org/MV2003-Present/Me15/Spacial-Baccelli.pdf

[1339] Connectivity and interferences in wireless ad-hoc networks, a percolation approach 0. Dousse www.terminodes.org/MV2003-Present/Me15/OlivierDousseMonteverita.pdf

[1340] Ad-hoc networks: the worst and the average case Prof. R. Wattenhofer www.terminodes.org/MV2003-Present/Me15/MV-Wattenhofer.pdf www.terminodes.org www.google.com/search?&q=terminodes www.ietf.org/html.charters/manet-charter.html. citeseer.nj.nec.com/cs?cs=1&q=manet&submit=Documents www.google.com/search?&q=%22ad+hoc%22+and+game citeseer.nj.nec.com/cs?cs=1&q=game+and+%22ad+hoc%22 carmen.cselt.it/idxwg/manet.html

[1352] The present invention seeks to apply aspects of game theory to the enhancement or optimization of communities. These communities may themselves have various rules, arrangements or cultures, which can be respected or programmed as a part of the system operation. These communities may be formed or employed for various purposes, and a preferred embodiment optimizes wireless communications in an open access band.

[1353] By optimizing communications, a greater communications bandwidth will generally be available, which will allow richer communications. This, in turn, permits new applications which depend on communications.

[1354] In a typical auction, each player is treated fairly; that is, the same rules apply to each player, and therefore a single economy describes the process. The fair auction therefore poses challenges for an inherently hierarchal set of users, such as a military organization, where rank is accompanied by privilege. The net result, however, is a decided disadvantage to lower ranking agents. In a mobile ad hoc network, a real issue is user defection or non-compliance. For example, where a cost is imposed on a user for participating in the ad hoc network, e.g., battery power consumption, if the anticipated benefit does not exceed the cost, the user will simply turn off the device until actually needed. The result of mass defection will of course be the instability and failure of the ad hoc network itself, leading to decreased utility, even for those who gain an unfair advantage under the system. Thus, perceived fairness and net benefit is required to network success, assuming that defection or non-compliance are possible.

[1355] On the other hand, in military systems, the assertion of rank as a basis for priority is not itself arbitrary and capricious. Orders and communications from a central command are critical for the organization itself, and thus the lower ranking agents gain at least a peripheral benefit as their own chain of command employs their resources. Therefore, the difficulty in analyzing the application of a fair game to a hierarchal organization is principally a result of conceptualizing and aligning the individual incentives with those of the organization as a whole and the relationship between branches.

[1356] In establishing an economic system, a preliminary question is whether the system is microeconomic or macroeconomic; that is, whether the economy is linked to a real economy or insulated from it. One disadvantage of a real economy with respect to a peer relationship is that external wealth can override internal dynamics, thus diminishing the advantages to be gained by optimization, and potentially creating a perception of unfairness for less wealthy agents, at least until the system accomplishes a wealth redistribution. An artificial economy provides a solution for a peer network in which each node has an equal opportunity to gain control over the ad hoc network, independent of outside influences.

[1357] In this proposed artificial economy, each node has a generator function for generating economic units, which are then used in an auction with other nodes to create a market economy. The economic units have a temporally and spatially declining value, so that wealth does not accumulate over long periods and cannot be transferred over large distances. This creates a set of microeconomies insulated from each other. Where distant microeconomies must deal with each other, there is a discount.

[1358] I propose that this scheme may be extended to the hierarchal case by treating branch within the chain of command as an economic unit with respect to the generator function. At any level of the hierarchy, the commander retains a portion of the wealth generation capacity, and delegates the remainder to its subordinates. Therefore, the rank and hierarchal considerations are translated to an economic wealth (or wealth generation) distribution. One aspect of this system allows wealth transfer or redistribution, although in a real system, a time delay is imposed, and in the event of a temporally and/or spatially declining value, the transfer will impose a cost. Thus, an initial misallocation is undesired, and there will be an incentive to optimally distribute the wealth initially.

[1359] In this system, there may be an economic competitive distortion, under which a node's subjective value of a resource is influenced by its then subjective wealth. If a node is supplied with wealth beyond its needs, the wealth is wasted, since it declines in value and cannot be hoarded indefinitely. If a node is supplied with insufficient wealth, economic surplus through transactional gains are lost. Thus, each node must analyze its expected circumstances to retain or delegate the generator function, and to optimally allocate wealth between competing subordinates. Likewise, there may be a plurality of quasi-optimal states.

[1360] In any transaction, there will be a component which represents the competitive “cost”, and a possible redistribution among nodes within a hierarchal chain. This redistribution may be of accumulated wealth, or of the generation function portion. Trading among hierarchally related parties is preferred, since the perceived cost is low, and the wealth can be repeatedly redistributed. In fact, it is because of the possibility of wealth oscillation and teaming that the declining wealth function is preferred, since this will tend to defeat closely related party control over the network for extended periods.

[1361] It is noted that, in a multihop mobile ad hoc network, if a communication path fails, no further transfers are possible, potentially resulting in stalled or corrupt system configuration. It is possible to transfer an expiring or declining portion of the generating function; however, this might lead a node which is out of range to have no ability to rejoin the network upon return, and thus act as an impediment to efficient network operation.

[1362] In practice, the bulk of the wealth generating function will be distributed to the lowest ranks with the highest numbers. Thus, under normal circumstances, the network will appear to operate according to a non-hierarchal model, with the distortion that not all nodes have a common generator function. On the other hand, hierarchically superior nodes either retain, or more likely, can quickly recruit surrounding subordinates to allocate their wealth generating function and accumulated wealth to pass urgent or valuable messages.

[1363] One way that this allocation of wealth may be apparent is through the use of expensive assets. Thus, a high level node might have access to a high power broadcast system, while low level nodes might ordinarily be limited to cellular wireless communications. For a low level node to generate a broadcast using an expensive asset (or to allocate a massive amount of space.bandwidth product, it must pass the request up through the chain of command, until sufficient wealth (i.e., authority) is available to implement the broadcast.

[1364] In fact, such communications and authorizations are quite consistent with the expectations within a hierarchal organization, and this construct is likely to be accepted.

[1365] Under normal circumstances, a superior would have an incentive to assure that each subordinate node possesses sufficient wealth to carry out its function and be incentivized to participate in the network. If a subordinate has insufficient initial wealth (or wealth generating function) allocation, it may still participate, but it must expend its internal resources to obtain wealth for participation in its own benefit. This, in turn, leads to a potential exhaustion of resources, and the unavailability of the node for ad hoc intermediary use, even for the benefit of the hierarchy. An initial surplus allocation will lead to overbidding for resources, and thus inefficient resource allocation, potential waste of allocation, and a disincentive to act as an intermediary in the ad hoc network.

[1366] In a military system, it is clearly possible to formulate an “engineered” solution which forces participation and eliminates defection; however, it is clear that such solutions forfeit the potential gains of optimality, and incentivizes circumvention. Further, because such a system is not “cost sensitive” (however the appropriate cost function might be expressed), it fails to respond to “market” forces.

[1367] Accordingly, a peer to peer mobile ad hoc network suitable for respecting hierarchal organization structures is delegation is provided.

[1368] Multihop Ad Hoc Networks require cooperation of nodes which are relatively disinterested in the content being conveyed. Typically, such disinterested intermediaries incur a cost for participation, for example, power consumption or opportunity cost. Economic incentives may be used to promote cooperation of disinterested intermediaries. An economic optimization may be achieved using a market-finding process, such as an auction. In many scenarios, the desire for the fairness of an auction is tempered by other concerns, i.e., there are constraints on the optimization which influence price and parties of a transaction. For example, in military communication systems, rank may be deemed an important factor in access to, and control over, the communications medium. A simple process of rank-based preemption, without regard for subjective or objective importance, will result in an economic distortion. In order to normalize the application of rank, one is presented with two options: imposing a normalization scheme with respect to rank to create a unified economy, or providing considering rank using a set of rules outside of the economy. One way to normalize rank, and the implicit hierarchy underlying the rank, is by treating the economy as an object oriented hierarchy, in which each individual inherits or is allocated a subset of the rights of a parent, with peers within the hierarchy operating in a purely economic manner. The extrinsic consideration of rank, outside of an economy, can be denominated “respect”, which corresponds to the societal treatment of the issue, rather than normalizing this factor within the economy, in order to avoid unintended secondary economic distortion. Each system has its merits and limitations.

[1369] An economic optimization is one involving a transaction in which all benefits and detriments can be expressed in normalized terms, and therefore by balancing all factors, including supply and demand, at a price, an optimum is achieved. Auctions are well known means to achieve an economic optimization between distinct interests, to transfer a good or right in exchange for a market price. While there are different types of auctions, each having their limitations and attributes, as a class these are well accepted as a means for transfer of goods or rights at an optimum price. Where multiple goods or rights are required in a sufficient combination to achieve a requirement, a so-called Vickrey-Clarke-Groves (VCG) auction may be employed. In such an auction, each supplier asserts a desired price for his component. The various combinations which meet the requirement are then compared, and the lowest selected. In a combinatorial supply auction, a plurality of buyers seek a divisible commodity, and each bids its best price. The bidders with the combination of prices which is maximum is selected. In a commodity market, there are a plurality of buyers and sellers, so the auction is more complex. In a market economy, the redistribution of goods or services are typically transferred between those whoe value them least to those who value them most. The transaction price depends on the balance between supply and demand; with the surplus being allocated to the limiting factor.

[1370] A previous scheme proposes the application of game theory in the control of mulotihop mobile ad hoc networks according to “fair” principles. In this prior scheme, nodes seeking to control the network (i.e., are “buyers” of bandwidth), conduct an auction for the resources desired. Likewise, potential intermediate nodes conduct an auction to supply the resources. The set of winning bidders and winning sellers is optimized to achieve the maximum economic surplus. Winning bidders pay the maximum bid price or second price, while winning sellers receive their winning ask or second price. The remaining surplus is redistributed among losing bidders, whose cooperation and non-interference with the winning bidders is required for network operation, in accordance with their proportionate bid for contested resources. The winning bids are determined by a VCG combinatorial process. The result is an optimum network topology with a reasonable, but by no means the only, fairness criterion, while promoting network stability and utility.

[1371] One issue with such a fair allocation of resources is that it does not readily permit intentional distortions. However, in some instances, a relatively extrinsic consideration to supply and subjective demand may be a core requirement of a system. For example, in military systems, it is traditional and expected that higher military rank will provide access to and control over resources on a favored basis. In civilian systems, emergency and police use may also be considered privileged. However, by seeking to apply economic rules to this access, a number of issues arise. Most significantly, as a privileged user disburses currency, this is distributed to unprivileged users, leading to an inflationary effect and comparative dilution of the intended privilege. If the economy is real, that is the currency is linked to a real economy, this grant of privilege will incur real costs, which is also not an intended effect. If the economy is synthetic, that is, it is unlinked to external economies, then the redistribution of wealth within the system can grant dramatic and undesired control to a few nodes, potentially conveying the privilege to those undeserving, except perhaps due to fortuitous circumstances.

[1372] Two different schemes may be used to address this desire for both economic optimality and hierarchal considerations. One scheme maintain optimality and fairness within the economic structure, but applies a generally orthogonal consideration of “respect” as a separate factor within the operation of the protocol. Respect is a subjective factor, and thus permits each bidder weight its own considerations. It is further noted that Buttyan et al. have discussed this factor as a part of an automated means for ensuring compliance with network rules, in the absence of a hierarchy. The bias introduced in the manner is created by an assertion by one claiming privilege, and deference by one respecting privilege. One way to avoid substantial economic distortions is to require that the payment made be based on a purely economic optimization, while selecting the winner based on other factors. In this way, the perturbations of the auction process itself is subtle, that is, since bidders realize that the winning bid may not result in the corresponding benefit, but incurs the publication of private values and potential bidding costs, there may be perturbation of the bidding strategy from optimal. Likewise, since the privilege is itself unfair and predictable, those with lower privilege ratings will have greater incentive to defect from, or act against, the network. Therefore, it is important that either the assertion of privilege be subjectively reasonable to those who must defer to it, or the incidence or impact of the assertions be uncommon or have low anticipated impact on the whole.

[1373] In the extreme case, the assertion of privilege will completely undermine the auction optimization, and the system will be prioritized on purely hierarchal grounds, and the pricing suboptimal or unpredictable. This condition may be acceptable or even efficient in military systems, but may be unacceptable where the deference is voluntary and choice of network protocol is available.

[1374] It is noted that those seeking access based on respect, must still make an economic bid. This bid, for example, should be sufficient in the case that respect is not afforded, for example, from those of equal rank or above, or those who for various reasons have other factors that override the assertion of respect. Therefore, one way to determine the amount of respect to be afforded is the self-worth advertised for the resources requested. This process therefore minimizes the deviation from optimal and therefore promotes stability of the network. It is further noted that those who assert respect based on hierarchy typically have available substantial economic resources, and therefore it is largely a desire to avoid economic redistribution rather than an inability to effect such a redistribution, that compels a consideration of respect.

[1375] In a combinatorial auction, each leg of a multihop link is separately acquired and accounted. Therefore, administration of the process is quite involved. That is, each bidder broadcasts a bid, and an optimal network with maximum surplus is defined. Each leg of each path is therefore allocated a value. Accordingly, if a bidder seeks to acquire the route, even though it was an insufficient economic bidder, but awarded the route based on respect, then those who must defer or accept reduced compensation must acquiesce based on deference, which is neither mandated nor uniform. If pricing is defined by the economic optimization, then the respect consideration requires that a subsidy be applied, either as an excess payment up to the amount of the winning bid, or as a discount provided by the sellers, down to the actually bid value. Since we presume that a surplus exists, this value may be applied to meet the gap, while maintaining optimal valuation. The node demanding respect may have an impact on path segments outside the required route; and thus the required payment to meet the differential between the optimum network and the resulting network may this be significant. If there is insufficient surplus, then a different strategy may be applied.

[1376] Since the allocation of respect is subjective, each bidder supplies a bid, as well as an assertion of respect. Each supplier receives the bids, and applies a weighting or discount based on its subjective analysis of the respect assertion. In this case, the same bid is interpreted differently by each supplier, and the subjective analysis must be performed by or for each supplier. By converting the respect assertion into a subjective weighting or discount, a pure economic optimization may then be performed.

[1377] An alternate scheme for hierarchal deference is to organize the economy itself into a hierarchy. In a hierarchy, a node has one parent and possibly multiple children. At each level, a node receives an allocation of wealth from its parent, and distributes all or a portion of its wealth to children. A parent is presumed to control its children, and therefore can allocate their wealth or subjective valuations to its own ends. When nodes representing different lineages must be reconciled, one may refer to the common ancestor for arbitration, or a set of inherited rules to define the hierarchal relationships.

[1378] In this system, the resources available for reallocation between branches of the hierarchy depends on the allocation by the common grandparent, as well as competing allocations within the branch. This system presumes that children communicate with their parents and are obedient. In fact, if the communication presumption is violated, one must then rely on a priori instructions, which may not be sufficiently adaptive to achieve an optimal result. If the obedience presumption is violated, then the hierarchal deference requires an enforcement mechanism within the hierarchy. If both presumptions are simultaneously violated, then the system will likely fail, except on a voluntary basis, with results similar to the “reputation” scheme described above.

[1379] Thus, it is possible to include hierarchal deference as a factor in optimization of a multihop mobile ad hoc network, leading to compatibility with tiered organizations, as well as with shared resources.

[1380] Game Theory

[1381] Use of Game Theory to control arbitration of ad hoc networks is well known [1,2]. Some prior studies have focused on the incremental cost to each node for participation in the network, without addressing the opportunity cost of a node foregoing control over the communication medium [3]. The present paper adds a new dimension to this analysis.

[1382] A game theoretic approach addresses the situation where the operation of an agent which has freedom of choice, allowing optimization on a high level, considering the possibility of alternatives to a well designed system. According to game theory, the best way to ensure that a system retains compliant agents, is to provide the greatest anticipated benefit, at the least anticipated cost, compared to the alternates.

[1383] Game Theory provides a basis for understanding the actions of Ad hoc network nodes. A multihop ad hoc network requires a communication to be passed through a disinterested node. The disinterested node incurs some cost, thus leading to a disincentive to cooperate. Meanwhile, bystander nodes must defer their own communications in order to avoid interference, especially in highly loaded networks. By understanding the decision analysis of the various nodes in a network, it is possible to optimize a system which, in accordance with game theory, provides benefits or incentives, to promote network reliability and stability. The incentive, in economic form, may be charged to those benefiting from the communication, and is preferably related to the value of the benefit received. The proposed network optimization scheme employs a modified combinatorial (VCG) auction, which optimally compensates those involved in the communication, with the benefiting party paying the second highest bid price (second price). The surplus between the second price and VCG price is distributed among those who defer to the winning bidder according to respective bid value. Equilibrium usage and headroom may be influenced by deviating from a zero-sum condition. The mechanism seeks to define fairness in terms of market value, providing probable participation benefit for all nodes, leading to network stability.

[1384] Ad Hoc Networks

[1385] An ad hoc network is a wireless network which does not require fixed infrastructure or centralized control. The terminals in the network cooperate and communicate with each other, in a self organizing network. In a multihop network, communications can extend beyond the scope of a single node, employing neighboring nodes to forward messages to their destination. In a mobile ad hoc network, constraints are not placed on the mobility of nodes, that is, they can relocate within a time scale which is short with respect to the communications, thus requiring consideration of dynamic changes in network architecture.

[1386] Ad hoc networks pose control issues with respect to contention, routing and information conveyance. There are typically tradeoffs involving equipment size, cost and complexity, protocol complexity, throughput efficiency, energy consumption, and “fairness” of access arbitration. Other factors may also come into play [4-10].

[1387] Game theory studies the interactions of multiple independent decision makers, each seeking to fulfill their own objectives. Game theory encompasses, for example, auction theory and strategic decision-making. By providing appropriate incentives, a group of independent actors may be persuaded, according to self-interest, to act toward the benefit of the group. That is, the selfish individual interests are aligned with the community interests. In this way, the community will be both efficient and the network of actors stable and predictable. Of course, any systems wherein the “incentives” impose too high a cost, themselves encourage circumvention. In this case, game theory also addresses this issue.

[1388] In computer networks, issues arise as the demand for communications bandwidth approaches the theoretical limit. Under such circumstances, the behavior of nodes will affect how close to the theoretical limit the system comes, and also which communications are permitted. The well known collision sense, multiple access (CSMA) protocol allows each node to request access to the network, essentially without cost or penalty, and regardless of the importance of the communication. While the protocol incurs relatively low overhead and may provide fully decentralized control, under congested network conditions, the system may exhibit instability, that is, a decline in throughput as demand increases, resulting in ever increasing demand on the system resources and decreasing throughput [11]. According to game theory, the deficit of the CSMA protocol is that it is a dominant strategy to be selfish and hog resources, regardless of the cost to society, resulting in “the tragedy of the commons.” [12]

[1389] In an ad hoc network used for conveying real-time information, as might be the case in a telematics system, there are potentially unlimited data communication requirements (e.g., video data), and network congestion is almost guaranteed. Therefore, using a CSMA protocol as the paradigm for basic information conveyance is destined for failure, unless there is a disincentive to network use. (In power constrained circumstances, this cost may itself provide such a disincentive). On the other hand, a system which provides more graceful degradation under high load, sensitivity to the importance of information to be communicated, and efficient utilization of the communications medium would appear more optimal.

[1390] One way to impose a cost which varies in dependence on the societal value of the good or service, is to conduct an auction, which is a mechanism to determine the market value of the good or service, at least between the auction participants [13]. In an auction, the bidder seeks to bid the lowest value, up to a value less than or equal to his own private value (the actual value which the bidder appraises the good or service, and above which there is no surplus), that will win the auction. Since competitive bidders can minimize the gains of another bidder by exploiting knowledge of the private value attached to the good or service by the bidder, it is generally a dominant strategy for the bidder to attempt to keep its private value a secret, at least until the auction is concluded, thus yielding strategies that result in the largest potential gain. On the other hand, in certain situations, release or publication of the private value is a dominant strategy, and can result in substantial efficiency, that is, honesty in reporting the private value results in the maximum likelihood of prospective gain.

[1391] Application of Game Theory to Ad Hoc Networks

[1392] There are a number of aspects of ad hoc network control which may be adjusted in accordance with game theoretic approaches. An example of the application of game theory to influence system architecture arises when communications latency is an issue. A significant factor in latency is the node hop count. Therefore, a system may seek to reduce node hop count by using an algorithm other than a nearest neighbor algorithm, bypassing some nodes with longer distance communications. In analyzing this possibility, one must not only look at the cost to the nodes involved in the communication, but also the cost to nodes which are prevented from simultaneously accessing the network dude to interfering uses of network resources. As a general proposition, the analysis of the network must include the impact of each action, or network state, on every node in the system, although simplifying presumptions may be appropriate where information is unavailable, or the anticipated impact is trivial.

[1393] Game theory is readily applied in the optimization of communications routes through a defined network, to achieve the best economic surplus allocation. In addition, the problem of determining the network topology, and the communications themselves, are ancillary, though real, applications of game theory. Since the communications incidental to the arbitration require consideration of some of the same issues as the underlying communications, corresponding elements of game theory may apply at both levels of analysis. Due to various uncertainties, the operation of the system is stochastic. This presumption, in turn, allows estimation of optimality within a margin of error, simplifying implementation as compared to a rigorous analysis without regard to statistical significance.

[1394] There are a number of known and proven routing models proposed for forwarding of packets in ad hoc networks. These include Ad Hoc On-Demand Distance Vector (AODV) Routing, Optimized Link State Routing Protocol (OLSR), Dynamic Source Routing Protocol (DSR), and Topology Dissemination Based on Reverse-Path Forwarding (TBRPF) [14-26]. In most systems analyzed to date, the performance metrics studied were power consumption, end-to-end data throughput and delay, route acquisition time, percentage out-of-order delivery, and efficiency. A critical variable considered in many prior studies is power cost, presuming a battery operated transceiver with limited power availability [27-32]. There can be significant differences in optimum routing depending on whether a node can modulate its transmit power, which in turn controls range, and provides a further control over network topology. Likewise, steerable antennas, antenna arrays, and other forms of multiplexing provide further degrees of control over network topology. Note that the protocol-level communications are preferably broadcasts, while information conveyance communications are typically point-to-point. Prior studies typically presume a single transceiver, with a single omnidirectional antenna, operating according to in-band protocol data, for all communications. The tradeoff made in limiting system designs according to these presumptions should be clear.

[1395] It is the general self-interest of a node to conserve its own resources, maintain an opportunity to access network resources, while consuming whatever resource of other nodes as it desires. Clearly, this presents a significant risk of the “tragedy of the commons”, in which selfish individuals fail to respect the very basis for the community they enjoy, and a network of rational nodes operating without significant incentives to cooperate would likely fail. On the other hand, if donating a node's resources generated a sufficient associated benefit to that node, while consuming network resources imposed a sufficient cost, stability and reliability can be achieved. So long as the functionality is sufficient to meet the need, and the economic surplus is “fairly” allocated, that is, the cost incurred is less than the private value of the benefit, and that cost is transferred as compensation to those burdened in an amount in excess of their incremental cost, adoption of the system should increase stability. In fact, even outside of these bounds, the system may be more stable than one which neither taxes system use nor rewards altruistic behavior. While the basic system is a zero sum system, and over time, the economic effects will likely average out (assuming symmetric nodes), in any particular instance, the incentive for selfish behavior by a node will be diminished.

[1396] One way to remedy selfish behavior is to increase the cost of acting this way, that is, to impose a cost or tax for access to the network. In a practical implementation, however, this is problematic, since under lightly loaded conditions, the “value” of the communications may not justify a fixed cost which might be reasonable under other conditions, and likewise, under heavier loads, critical communications may still be delayed or impeded. A variable cost, dependent on relative “importance”, may be imposed, and indeed, as alluded to above, this cost may be market based, in the manner of an auction. In a multihop network, such an auction is complicated by the requirement for a distribution of payments within the chain of nodes, with each node having potential alternate demands for its cooperation. The market-based price-finding mechanism excludes nodes which ask a price not supported by its market position, and the auction itself may comprise a value function encompassing reliability, latency, quality of service, or other non-economic parameters, in economic terms. The network may further require compensation to nodes which must defer communications because of inconsistent states, such as in order to avoid interference or duplicative use of an intermediary node, and which take no direct part in the communication. It is noted that the concept of the winner of an auction paying the losers is not well known, and indeed somewhat counterintuitive. Indeed, the effect of this rule perturbs the traditional analysis framework, since the possibility of a payment from the winner to the loser alters the allocation of economic surplus between the bidder, seller, and others. Likewise, while the cost to the involved nodes may be real, the cost to the uninvolved nodes may be subjective. Clearly, it would appear that involved nodes should generally be better compensated than uninvolved nodes, although a rigorous analysis remains to be performed.

[1397] The network provides competitive access to the physical transport medium, and cooperation with the protocol provides significant advantages over competition with it. Under normal circumstances, a well developed ad hoc network system can present as a formidable coordinated competitor for access to contested bandwidth by other systems, while within the network, economic surplus is optimized. Thus, a node presented with a communications requirement is presented not with the simple choice to participate or abstain, but rather whether to participate in an ad hoc network with predicted stability and mutual benefit, or one with the possibility of failure due to selfish behavior, and non-cooperation. Even in the absence of a present communication requirement, a network which rewards cooperative behavior may be preferable to one which simply expects altruism.

[1398] The protocol may also encompass the concept of node reputation, that is, a positive or negative statement by others regarding the node in question [33]. This reputation may be evaluated as a parameter in an economic analysis, or applied separately, and may be anecdotal or statistical. In any case, if access to resources and payments are made dependent on reputation, nodes will be incentivized to maintain a good reputation, and avoid generating a bad reputation. Therefore, by maintaining and applying the reputation in a manner consistent with the community goals, the nodes are compelled to advance those goals in order to benefit from the community. Game theory distinguishes between good reputation and bad reputation. Nodes may have a selfish motivation to assert that another node has a bad reputation, while it would have little selfish motivation, absent collusion, for undeservedly asserting a good reputation. On the other hand, a node may have a selfish motivation in failing to reward behavior with a good reputation.

[1399] Economics and reputation may be considered orthogonal, since the status of a node's currency account provides no information about the status of its reputation.

[1400] This reputation parameter may be extended to encompass respect, that is, a subjective deference to another based on an asserted or imputed entitlement. While the prior system uses reputation as a factor to ensure compliance with system rules, this can be extended to provided deferential preferences either within or extrinsic to an economy. Thus, in a military hierarchy, a relatively higher ranking official can assert rank, and if accepted, override a relatively lower ranking bidder at the same economic bid. For each node, an algorithm is provided to translate a particular assertion of respect (i.e., rank and chain of command) into an economic perturbation. For example, in the same chain of command, each difference in rank might be associated with a 25% compounded discount, when compared with other bids, i.e.
B₁=B₀×10(1+0.25×ΔR),
while outside the chain of command, a different, generally lower, discount may be applied, possibly with a base discount as compared to all bids within the chain of command, i.e.,
B₁=B₀×10(1+dCOC+dNCOC×ΔR).
The discount is applied so that higher ranking officers pay less, while lower ranking officers pay more. Clearly, there is a high incentive for each bid to originate from the highest available commander within the chain of command, and given the effect of the perturbation, for ranking officers to “pull rank” judiciously.

[1401] The Modified VCG Auction

[1402] A so-called Vickrey-Clarke-Groves, or VCG, auction, is a type of auction suitable for bidding, in a single auction, for the goods or services of a plurality of offerors, as a unit [34-47]. In the classic case, each bidder bids a value vector for each available combination of goods or services. The various components and associated ask price are evaluated combinatorially to achieve the minimum sum to meet the requirement. The winning bid set is that which produces the maximum value of the accepted bids, although the second (Vickrey) price is paid. In the present context, each offeror submits an ask price (reserve) or evaluatable value function for a component of the combination. If the minimum aggregate to meet the bid requirement is not met, the auction fails. If the auction is successful, then the set of offerors selected is that with the lowest aggregate bid, and they are compensated that amount.

[1403] The VCG auction is postulated as being optimal for allocation of multiple resources between agents. It is “strategyproof” and efficient, meaning that it is a dominant strategy for agents to report their true valuation for a resource, and the result of the optimization is a network which maximizes the value of the system to the agents. Game theory also allows an allocation of cost between various recipients of a broadcast or multicast. That is, the communication is of value to a plurality of nodes, and a large set of recipient nodes may efficiently receive the same information. This allocation from multiple bidders to multiple sellers is a direct extension of VCG theory, and a similar algorithm may be used to optimize allocation of costs and benefit.

[1404] The principal issue involved in VCG auctions is that the computational complexity of the optimization grows with the number of buyers and their different value functions and allocations. While various simplifying presumptions may be applied, studies reveal that these simplifications may undermine the VCG premise, and therefore do not promote honesty in reporting the buyer's valuation, and are thus not “strategyproof”, which is a principal advantage of the VCG process.

[1405] The surplus, i.e., gap between bid and ask, is then available to compensate the deferred bidders. This surplus is distributed proportionately to original the bid value for the bidder, thus further encouraging an honest valuation of control over the resource.

[1406] The optimization is such that, if any offeror asks an amount that is too high, it will be bypassed in favor of more “reasonable” offerors. Since the bidder pays the second highest price, honesty in bidding the full private value is encouraged. The distribution of the surplus to losing bidders, which exercise deference to the winner, is proportional to the amount bid, that is, the reported value.

[1407] In a scenario involving a request for information meeting specified criteria, the auction is complicated by the fact that the information resource content is unknown to the recipient, and therefore the bid is blind, that is, the value of the information to the recipient is indeterminate. However, game theory supports the communication of a value function or utility function, which can then be evaluated at each node possessing information to be communicated, to normalize its value. Fortunately, it is a dominant strategy in a VCG auction to communicate a truthful value, and therefore broadcasting the private value function, to be evaluated by a recipient, is not untenable. In a mere request for information conveyance, such as the transport nodes in a multihop network, or in a cellular network infrastructure extension model, the bid may be a true (resolved) value, since the information content is not the subject of the bidding; rather it is the value of the communications per se, and the bidding node can reasonably value its bid.

[1408] Game theory also allows an allocation of cost between various recipients of a broadcast or multicast. That is, in many instances, information which is of value to a plurality of nodes, and a large set of recipient nodes may efficiently receive the same information. This allocation is a direct extension of VCG theory.

[1409] Operation of Protocol

[1410] The preferred method for acquiring an estimate of the state of the network is through use of a proactive routing protocol. Thus, in order to determine the network architecture state, each node must broadcast its existence, and, for example, a payload of information including its identity, location, itinerary (navigation vector) and “information value function”. Typically, the system operates in a continuous state, so that it is reasonable to commence the process with an estimate of the state based on prior information. Using an in-band or out-of-band propagation mechanism, this information must propagate to a network edge, which may be physically or artificially defined. If all nodes operate with a substantially common estimation of network topology, only deviations from previously propagated information need be propagated.

[1411] CSMA is proposed for the protocol-related communications because it is relatively simple and robust, and well suited for ad hoc communications in lightly loaded networks. An initial node transmits using an adaptive power protocol, to achieve an effective transmit range of somewhat less than about two times the estimated average inter-nodal distance. This distance therefore promotes propagation to a set of neighboring nodes, without unnecessarily interfering with communications of non-neighboring nodes and therefore allowing this task to be performed in parallel. Neighboring nodes also transmit in succession, providing sequential and complete protocol information propagation over a relevance range.

[1412] If we presume that there is a spatial limit to relevance, for example, 5 miles or 10 hops, then the network state propagation may be so limited. Extending the network to encompass a large number of nodes will necessarily reduce the tractability of the optimization. Each node has a local estimate of relevance. This consideration is accommodated, along with a desire to prevent exponential growth in protocol-related data traffic, by receiving an update from all nodes within a node's network relevance boundary, and a state variable which represents an estimate of relevant status beyond the arbitrarily defined boundary. The propagation of network state may thus conveniently occur over a finite number of hops, for example 5-10.

[1413] Under conditions of relatively high nodal densities, the system may employ a zone strategy, that is, proximate groups of nodes are is treated as an entity for purposes of external state estimation, especially with respect to distant nodes or zones. Such a presumption is realistic, since at extended distances, geographically proximate nodes may be modeled as being similar or inter-related, while at close distances, and particularly within a zone in which all nodes are in direct communication, inter-node communications may be subject to mutual interference, and can occur without substantial external influence. Alternately, it is clear that to limit latencies and communication risks, it may be prudent to bypass neighboring nodes, thus trading latency for power consumption and overall network capacity. Therefore, a hierarchal scheme may be implemented to geographically organize the network at higher analytical levels, and geographic cells may cooperate to appear externally as a single entity.

[1414] A supernode within a zone may be selected for its superior capability, or perhaps a central location. The zone is defined by a communication range of the basic data interface for communications, with the control channel having a longer range, for example at least double the normal data communications range. Communications control channel transmitters operate on a number of channels, for example at least 7, allowing neighboring zones in a hexagonal tiled array to communicate simultaneously without interference. In a geographic zone system, alternate zones which would otherwise be interfering may use an adaptive multiplexing scheme to avoid interference. All nodes may listen on all control channels, permitting rapid propagation of control information.

[1415] In order to effective provide decentralized control, either each node must have a common set of information to allow execution of an identical control algorithm, or nodes defer to the control signals of other nodes without internal analysis for optimality. A model of semi-decentralized control is also known, in which dispersed supernodes are nominated as master, with other topologically nearby nodes remaining as slave nodes. In the pure peer network, complete information conveyance to each node is required, imposing a relatively high overhead. In a master-slave (or supernode) architecture, increased reliance on a single node trades-off reliability and robustness (and other advantages of pure peer-to-peer networks) for efficiency. A supernode within a cellular zone may be selected for its superior capability, or perhaps is at a central location or is immobile.

[1416] Once each control node (node or supernode) has an estimate of network topology, the next step is to optimize network channels. According to VCG theory, each agent has an incentive to broadcast its truthful value or value function for the scarce resource, which in this case, is control over communications physical layer, and or access to information. This communication can be consolidated with the network discovery transmission. Each control node then performs a combinatorial solution for the set of simultaneous equations according to VCG theory (or extensions thereof). This solution should be consistent between all nodes, and the effects of inconsistent solutions may be resolved by collision sensing, and possibly an error/inconsistency detection and correction algorithm specifically applied to this type of information.

[1417] As part of the network mapping, communications impairment and interference sources are also mapped. GPS assistance may be particularly useful in this aspect. Where interference is caused by interfering communications, the issue is a determination of a strategy of deference or competition. If the interfering communication is continuous or unresponsive, then the only available strategy is competition. On the other hand, when the competing system uses, for example, a CSMA system, such as 802.11, competition with such a communication simply leads to retransmission, and therefore ultimately increased network load, and deference strategy may be more optimal, at least and until it is determined that the competing communication is incessant. Other communications protocols, however may have a more or less aggressive strategy. By observation of a system over time, its strategies may be revealed, and game theory permits composition of an optimal strategy to deal with interference or coexistence.

[1418] The optimization process produces a representation of optimal network architecture during the succeeding period. That is, value functions representing bids are broadcast, with the system then being permitted to determine an optimal real valuation and distribution of that value. Thus, prior to completion of the optimization, potentially inconsistent allocations must be prevented, and each node must communicate its evaluation of other node's value functions, so that the optimization is performed on a normalized economic basis. This step may substantially increase the system overhead, and is generally required for completion of the auction. This valuation may be inferred, however, for intermediate nodes in a multihop network path, since there is little subjectivity for nodes solely in this role, and the respective value functions may be persistent. For example, the valuation applied by a node to forward information is generally independent of content and involved party.

[1419] After the network architecture is defined, compensation is paid to those nodes providing value or subjected to a burden (including foregoing communication opportunity) by those gaining a benefit. The payment may be a virtual currency, with no specific true value, although the virtual currency system provides a convenient method to tax, subsidize, or control the system, and thus apply a normalized extrinsic value.

[1420] Using the protocol communication system, each node transmits its value function (or change thereof), passes through communications from neighboring nodes, and may, for example transmit payment information for the immediate-past bid for incoming communications.

[1421] Messages are forwarded outward (avoiding redundant propagation back to the source), with messages appended from the series of nodes. Propagation continues for a finite number of hops, until the entire community has an estimate of the state and value function of each node in the community. Advantageously, the network beyond a respective community may be modeled in simplified form, to provide a better estimate of the network as a whole.

[1422] After propagation, each node evaluates the set of value functions for its community, with respect to its own information and ability to forward packets. Each node may then make an offer to supply or forward information, based on the provided information. In the case of multihop communications, the offers are propagated to the remainder of the community, for the maximum number of hops, including the originating node. At this point, each node has a representation of the state of its community, with community edge estimates providing consistency for nodes with differing community scopes, the valuation function each node assigns to control over portions of the network, as well as a resolved valuation of each node for supplying the need. Under these circumstances, each node may then evaluate an optimization for the network architecture, and come to a conclusion consistent with that of other members of its community. If supported, node reputation may be updated based on past performance, and the reputation applied as a factor in the optimization and/or externally to the optimization. As discussed above, a VCG-type auction is employed as a basis for optimization. Since each node receives bid information from all other nodes within the maximum node count, the VCG auction produces an optimized result.

[1423] Transmissions are made in frames, with a single bidding process controlling multiple frames, for example a multiple of the maximum number of hops. Therefore, the bid encompasses a frame's-worth of control over the modalities. In the event that the simultaneous use of, or control over, a modality by various nodes is not inconsistent, then the value of the respective nodes may be summed, with the resulting allocation based on, for example, a ratio of the respective value functions. As a part of the optimization, nodes are rewarded not only for supporting the communication, but also for deferring their own respective needs. As a result, after controlling the resources, a node will be relatively less wealthy and less able to subsequently control the resources, while other nodes will be more able to control the resources. The distribution to deferred nodes also serves to prevent pure reciprocal communications, since the proposed mechanism distributes and dilutes the wealth to deferring nodes.

[1424] Because each node in the model presented above has complete information, for a range up to the maximum node count, the wealth of each node can be estimated by its neighbors, and payment inferred even if not actually consummated. (Failure of payment can occur for a number of reasons, including both malicious and accidental). Because each hop adds significant cost, the fact that nodes beyond the maximum hop distance are essentially incommunicado is typically of little consequence; since it is very unlikely that a node more than 5 or 10 hops away will be efficiently included in any communication, due to the increasing cost with distance, as well as reduction in reliability and increase in latency. Thus, large area and scalable networks may exist.

[1425] The Synthetic Economy

[1426] Exerting external economic influences on the system may have various effects on the optimization, and may exacerbate differences in subjective valuations. The application of a monetary value to the virtual currency substantially also increases the possibility of misbehavior and external attacks. On the other hand, a virtual currency with no assessed real value is self-normalizing, while monetization leads to external and generally irrelevant influences as well as possible arbitrage. External economic influences may also lead to benefits, which are discussed in various papers on non-zero sum games.

[1427] In order to provide fairness, the virtual currency (similar to the so-called “nuglets” or “nuggets” proposed for use in the Terminodes project) [48-55] is self-generated at each node according to a schedule, and itself may have a time dependent value. For example, the virtual currency may have a half-life or temporally declining value. On the other hand, the value may peak at a time after generation, which would encourage deference and short term savings, rather than immediate spending, and would allow a recipient node to benefit from virtual currency transferred before its peak value. This also means that long term hoarding of the currency is of little value, since it will eventually decay in value, while the system presupposes a nominal rate of spending, which is normalized among nodes. The variation function may also be adaptive, but this poses a synchronization issue for the network. An external estimate of node wealth may be used to infer counterfeiting, theft and failure to pay debts, and to further effect remediation.

[1428] The currency is generated and verified in accordance with micropayment theory [56-57]. Micropayment theory generally encompasses the transfer of secure tokens (e.g., cryptographically endorsed information) having presumed value, which are intended for verification, if at all, in a non-real time transaction, after the transfer to the recipient. The currency is circulated (until expiration) as a token, and therefore is not subject to immediate authentication by source. Since these tokens may be communicated through an insecure network, the issue of forcing allocation of payment to particular nodes may be dealt with by cryptographic techniques, in particular public key cryptography, in which the currency is placed in a cryptographic “envelope” addressed to the intended recipient, e.g., is encrypted with the recipient's public key, which must be broadcast and used as, or in conjunction with, a node identifier. This makes the payment unavailable to other than the intended recipient. The issue of holding the encrypted token hostage and extorting a portion of the value to forward the packet can be dealt with by community pressure, that is, any node presenting this (or other undesirable) behavior might be ostracized. The likelihood of this type of misbehavior is also diminished by avoiding monetization of the virtual currency.

[1429] This currency generation and allocation mechanism generally encourages equal consumption by the various nodes over the long term. In order to discourage consumption of bandwidth, an external tax may be imposed on the system, that is, withdrawing value from the system base on usage. Clearly, the effects of such a tax must be carefully weighed, since this will also impose an impediment to adoption as compared to an untaxed system. On the other hand, a similar effect use-disincentive may be obtained by rewarding low consumption, for example by allocating an advertising subsidy between nodes, or in reward of deference.

[1430] A synthetic economy affords the opportunity to provide particular control over the generator function, which in turn supports a hierarchy. In this scheme, each node controls the generator function at respectively lower nodes, and thus can allocate wealth among subordinates. If one assumes real time communications, then it is clear that the superordinate node can directly place bids on behalf of subordinates, thus effectively controlling its entire branch. In the absence of real time communications, the superordinate node must defer to the discretion of the subordinate, subject to reallocation later if the subordinate defects. If communications are impaired, and a set of a priori instructions are insufficient, then it is up to the subjective response of a node to provide deference.

[1431] It is noted that when sets of nodes “play favorites”, the VCG auction will no longer be considered “strategyproof”. The result is that bidders will assume bidding strategies that do not express their secret valuation, with the result being likely suboptimal market finding during the auction. This factor can be avoided if hierarchal overrides and group bidding play only a small role in the economy, and thus the expected benefits from shaded bidding are outweighed by the normal operation of the system.

[1432] Military Hierarchy

[1433] In a typical auction, each player is treated fairly; that is, the same rules apply to each player, and therefore a single economy describes the process. The fair auction therefore poses challenges for an inherently hierarchal set of users, such as a military organization. In the military, there is typically an expectation that rank has its privileges. The net result, however, is a decided subjective unfairness to lower ranking nodes. In a mobile ad hoc network, a real issue is user defection or non-compliance. For example, where a cost is imposed on a user for participating in the ad hoc network, e.g., battery power consumption, if the anticipated benefit does not exceed the cost, the user will simply turn off the device until actually needed. The result of mass defection will of course be the instability and failure of the ad hoc network itself. Thus, perceived fairness and net benefit is required to network success, assuming that defection or non-compliance are possible.

[1434] On the other hand, in military systems, the assertion of rank as a basis for priority is not arbitrary and capricious, and is generally not perceived subjectively as such. Orders and communications from a central command are critical for the organization itself. Therefore, the difficulty in analyzing the application of a fair game to a hierarchal organization is principally a result of conceptualizing and aligning the individual incentives with those of the organization as a whole.

[1435] An artificial economy provides a basis for an economically efficient solution. In this economy, each node has a generator function for generating economic units which are used in a combinatorial auction with other nodes. The economic units have a declining value, so that wealth does not accumulate over long periods, and by implication, wealth accumulated in one region is not available for transfer in a distant region.

[1436] This scheme may be extended to the hierarchal case by treating each chain of command as an economic unit with respect to the generator function. At any level of the hierarchy, the commander retains a portion of the wealth generation capacity, and delegates the remainder to its subordinates. In the case of real-time communications, a commander may directly control allocation of the generator function at each time period. Typically, there is no real-time communications capability, and the wealth generator function must be allocated a priori. Likewise, wealth may also be reallocated, although a penalty is incurred in the event of an initial misallocation since the transfer itself incurs a cost, and there will be an economic competitive distortion, under which a node's subjective value of a resource is influenced by its subjective wealth. If a node is supplied with wealth beyond its needs, the wealth is wasted, since it declines in value and cannot be hoarded indefinitely. If a node is supplied with insufficient wealth, economic surplus through transactional gains are lost. Thus, each node must analyze its expected circumstances to retain or delegate the generator function, and to optimally allocate wealth between competing subordinates.

[1437] In any transaction, there will be a component which represents the competitive “cost”, and a possible redistribution among nodes within a hierarchal chain. This redistribution may be of accumulated wealth, or of the generation function portion. In the former case, if the communication path fails, no further transfers are possible, while in the later case, the result is persistent until the transfer function allocation is reversed. It is also possible to transfer an expiring or declining portion of the generating function; however, this might lead a node which is out of range to have no ability to rejoin the network upon return, and thus act as an impediment to efficient network operation.

[1438] In practice, the bulk of the wealth generating function will be distributed to the lowest ranks with the highest numbers. Thus, under normal circumstances, the network will appear to operate according to a non-hierarchal VCG model, with the distortion that not all nodes have a common generator function. On the other hand, hierarchically superior nodes either retain, or more likely, can quickly recruit surrounding subordinates to allocate their wealth generating function and accumulated wealth to pass urgent or valuable messages.

[1439] One way that this allocation of wealth may be apparent is through the use of expensive assets. Thus, a high level node might have access to a high power broadcast system, while low level nodes might ordinarily be limited to cellular wireless communications. For a low level node to generate a broadcast using an expensive asset (or to allocate a massive amount of space.bandwidth product, it must pass the request up through the chain of command, until sufficient wealth (i.e., authority) is available to implement the broadcast.

[1440] In fact, such communications and authorizations are quite consistent with the expectations within a hierarchal organization, and this likely to be accepted.

[1441] Under normal circumstances, a superior would have an incentive to assure that each subordinate node possesses sufficient wealth to carry out its function and be incentivized to participate in the network. If a subordinate has insufficient initial wealth (or wealth generating function) allocation, it may still participate, but it must expend its internal resources to obtain wealth for participation in its own benefit. This, in turn, leads to a potential exhaustion of resources, and the unavailability of the node for ad hoc intermediary use, even for the benefit of the hierarchy. An initial surplus allocation will lead to overbidding for resources, and thus inefficient resource allocation, potential waste of allocation, and a disincentive to act as an intermediary in the ad hoc network.

[1442] In a military system, it is clearly possible to formulate an “engineered” solution which forces participation and eliminates defection; however, it is clear that such solutions forfeit the potential gains of optimality, and incentivized circumvention.

[1443] Cellular Network Extension

[1444] Cellular Networks provide efficient coverage of large portions of the inhabited landmass. On the other hand, achieving complete coverage, including relatively uninhabited areas, may be cost inefficient or infeasible. On the other hand, there remains significant unmet demand for coverage of certain areas.

[1445] Generally, it is likely that a need for service arises within a few miles from the edge of a cellular network. That is, the fixed infrastructure is almost in reach. On the other hand, the infrastructure costs required to fill in gaps or marginally extend the network may be inordinately high, for the direct economic benefits achieved. At present, there is no effective means for remediating these gaps.

[1446] One problem arises in that the present networks generally have a threshold usage plan. All territory encompassed by a network is treated as fungible, and incurs the same cost. Likewise, usage of partner networks is also treated as fungible. Therefore, the incentive to extend network reach for any company is limited to the overall incentive for customers to defect to different networks, balanced against the increased cost of extending the network. It is in the context of this economic problem that a solution is proposed. Quite simply, in the same areas where the cellular infrastructure is insufficient and there is demand for service, it may be possible to implement a peer-to-peer network or multihop network to extend a cellular network system. In fact, if we presume that the coverage is absent, the network extension function may make use of the licensed spectrum, thus making the transceiver design more efficient, and eliminating extrinsic competing uses for the bandwidth. On the other hand, different spectrum may be employed, which may be licensed or unlicensed.

[1447] Various studies have shown that modeled multihop mobile ad hoc network architectures tend to have low efficiency over three to five hops. This is due to node mobility and the probability of finding an end-to-end connection, mutual interference and competition for bandwidth in shared channel protocols, and the overhead of maintaining useful routing tables. If we take five hops as a reasonable maximum, and each transceiver has a 1000 meter range, then a 5 km maximum range extension is possible. It is believed that by extending the fringe of cellular networks by 3-5 km, a significant portion of the unmet demand for cellular service will be satisfied.

[1448] If we assume that a significant portion of the mobile nodes are power constrained (e.g., battery operated), that is, retransmission of packets imposes a power cost, then the stability of the mobile ad hoc network and cooperation with its requirements will depend on properly incentivizing intermediary nodes to allocate their resources to the network. Since this incentive is provided in a commercial context, that is, the cellular service is a commercial enterprise with substantial cash flow, a real economy with monetary incentives may be provided. Under such circumstances, it is relatively straightforward to allocate costs and benefits between the competing interests to achieve consistent and apparent incentives. On the other hand, the cost of this additional process must be commensurate with the benefits provided, or else the ad hoc network will become unreliable.

[1449] While the true economics of the costs and value functions for the participants are beyond the scope of this paper, some estimates are available. The issue is: are users willing to pay for extended cellular reach? If so, do they value the benefits commensurate with the overall costs, including service fees, hardware, and ad hoc cooperative burdens? As such, care must be exercised to define competitive compensation or the business will be inefficient. Since this extension is driven by the cellular network operator, a suitable return on investment is mandated.

[1450] Many analyses and studies have concluded that voluntary ad hoc networks are efficient when the incentives to cooperate with the network goals are aligned and sufficient to incentivize users accordingly. If the reward for cooperation is optimum, then the network will benefit by increased coverage and reliability, each node will benefit from increased utility, and intermediary nodes will specifically benefit through compensation. Due to the technical possibility for potential intermediaries to fail to either participate in network administration or operation, while taking advantage of the network as a beneficiary, the promotion of network availability as an incentive for cooperation is typically itself insufficient incentive to assure cooperation. The particular cost of the limited power resource for potential intermediaries makes non-cooperation a particularly important factor. On the other hand, the presumption of power cost as a critical factor may be accurate only in some circumstances: In many cases, a cheap power source is available, such as in a home or office, or in a vehicle, making other factors more important.

[1451] It is noted that, in a cellular telephone system, the reasonable acts of a user which might undermine the network are limited. Clearly, the user can choose a different network or provider. The user may turn off his phone or make it unavailable. The user may abuse the service contract, taking advantage of promotions or “free” access to the detriment of others. Notably, the user typically has no reasonable ability to reprogram the phone or alter its operation in accordance with the protocol, unless granted this option by the network operator. The user cannot reasonably compete or interfere with the licensed spectrum. While older analog cellular phones provided the user with an option to install power amplifiers and vehicle mount antennas, few current users employ these options.

[1452] If one limits the present system to a five hop distance from fixed cellular infrastructure (or more accurately, permits the system to deny service to nodes more than five hops away) then the routing requirements and node complexity may be substantially simplified. We also presume that each node has geolocation capability, and therefore can provide both its location and velocity vector. This is reasonable, since the FCC E911 mandate provides for geolocation of handsets within range of the cellular infrastructure, and GPS is a one option to provide this feature.

[1453] The ad hoc communications can occur using a licensed or unlicensed band. For example, since we presume that nodes are beyond range of a fixed cellular tower (except the closest node), the ad hoc network may reuse licensed bandwidth in the uncovered region. The ad hoc communications may also occur in unlicensed spectrum, such as the 2.4 GHz ISM band.

[1454] In order to provide optimum compensation, two issues are confronted. First, the total compensation paid; and second, the distribution of payments between the intermediaries. The VCG auction is a known means for optimizing a payment which must be distributed between a number of participants. In this case, each potential intermediary places a “bid”. A multi-factorial optimization is performed to determine the lowest cost set which provides sufficient services.

[1455] In a cellular system, each subscriber typically purchases a number of minute units on a monthly recurring charge basis. Compensation might therefore be based on minutes or money. Since there is a substantial disincentive to exceed the number of committed minutes, providing a surplus of minutes may not provide a significant incentive, because the user will rarely exceed the committed amount. Monetary incentives, on the other hand, must be coupled to a higher monthly recurring fee, since the proposal would by unprofitable otherwise.

[1456] A more direct scheme provides an economy for multihop networks somewhat independent from the cellular system economy. That is, nodes that participate as intermediary, may also participate as a principal to the information communication, while those who abstain from intermediary activities are denied access to the network extension as a principal.

[1457] While, on a theoretical basis, optimization of both price and distribution would be considered useful, in a practical system, it may be useful to make simplifying presumptions and simplifications. For example, while a VCG auction may provide an optimal cost and distribution of compensation, in a commercial network, a degree of certainty may actually prove advantageous. For example, a fixed compensation per hop or per milliWatt-second may prove both fair and reasonable.

[1458] Likewise, a degree of certainty over cost would be beneficial over an “optimal” cost. On the other hand, fixed cost and fixed compensation are inconsistent in a revenue neutral system. Even if the cellular carrier subsidizes the extension operation, there is little rationale for making the usage at the fringe insensitive to cost, other than the relief from uncertainty, which will tend to increase fringe usage, and the scope of the subsidy cost.

[1459] Therefore, it is realistic for a node requesting extension service to apply a value function to define a maximum payment for service. The payment is therefore dependent on system cost, alleviating the requirement for subsidy, but also dependent on need.

[1460] In the typical case, the load on the extension network will be low, since if demand were high, the fixed infrastructure would likely be extended to this region. On the other hand, there may be cases where demand is high, and therefore there is competition for access to the network, leading to a need to arbitrate access.

[1461] In general, where economic demand is high, there is a tendency to recruit new sources of supply. That is, the system may operate in two modes. In a first, low demand mode, costs are based on a relatively simple algorithm, with a monetary cap. In a second mode, costs are competitive (and in excess of the algorithmic level), with compensation also being competitive. The surplus, in this case, would generally be allocated to the cellular carrier, since this represents the commercial profit of the enterprise. The first mode also serves another purpose; under lightly loaded conditions, the market may be thin, and therefore pricing unstable. Therefore, the imposition of fixed pricing leads to reduced pricing risk.

[1462] In the second mode, an intended user specifies his demand as a maximum price and demand function, that is, a bid based on, for example, a value of the communication. Generally, this would be set by the user in advance as a static value or relatively simple function representing the contextual value of the communication. The actual price may be, for example, the bid price less otherwise attributable discount under the first mode based on the maximum number of hops, etc. The intermediate nodes set forth their bids in the manner of a VCG auction, with each bid presumably exceeding the first mode compensation. The VCG optimization may be corrected for quality of service factors and anticipated network stability.

[1463] Clearly, the economics of the system are substantially under the control of the cellular carrier, who may offer “plans” and “services” for their customers, thus providing an alternative to the usage-based bidding process, at least for some users. The VCG process, however, remains useful for compensating intermediaries.

[1464] The intermediary chooses its bid for providing packet forwarding services based on a number of factors, such as anticipated power cost, opportunity cost, etc. These bids are determined automatically, and therefore do not consume substantial human efforts.

[1465] Conclusion

[1466] Game theory is a useful basis for analyzing ad hoc networks, and understanding the behavior of complex networks of independent nodes. By presuming a degree of choice and decision-making by nodes, we obtain an analysis that is robust with respect to such considerations. The principal issues impeding deployment are the inherent complexity of the system, as well as the overhead required to continuously optimize the system. Further work will allow a determination of a set of simplifying presumptions to reduce protocol overhead and reduce complexity. Hierarchal considerations can be imposed to alter the optimization of the system, which would be expected to provide only a small perturbation to the efficient and optimal operation of the system according to a pure VCG protocol. This paper proposes a marketplace auction with competition between potential buyers and potential sellers, with the economic surplus distributed between parties which must defer to active participants.

[1467] The ad hoc network does not exist in a vacuum. There are various competing interests seeking to use the same bandwidth, and technological superiority alone does not assure dominance and commercial success. Game theory may also be used as a tool to analyze the entities which seek to deploy ad hoc networks, especially where they compete.

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[1525] A third embodiment of the invention, described below, represents a system which may employ a self-organizing network to convey information between mobile nodes. It is expressly understood that the concepts set forth above in the first and second embodiments are directly applicable, and each aspect of the third embodiment may be extended using the hierarchal principles and modifications, in a consistent manner, to achieve the advantages described herein. That is, while the third embodiment generally describes peer nodes, the extension of the systems and methods to non-peer nodes is specifically envisioned and encompassed.

[1526] This patent builds upon and extends aspects of U.S. Pat. No. 6,252,544 (Hoffberg), Jun. 26, 2001, and U.S. Pat. No. 6,429,812, Aug. 6, 2002, which are expressly incorporated herein by reference in its entirety. See, also, U.S. Pat. No. 6,397,141 (Binnig, May 28, 2002, Method and device for signalling local traffic delays), expressly incorporated herein by reference, which relates to a method and an apparatus for signalling local traffic disturbances wherein a decentralised communication between vehicles, which is performed by exchanging their respective vehicle data. Through repeated evaluation of these individual vehicle data, each reference vehicle may determine a group of vehicles having relevance for itself from within a maximum group of vehicles and compare the group behavior of the relevant group with its own behavior. The results of this comparison are indicated in the reference vehicle, whereby a homogeneous flow of traffic may be generated, and the occurrence of accidents is reduced. See, also U.S. Pat. No. 4,706,086 (November, 1987 Panizza 340/902), and U.S. Pat. No. 5,428,544 (June, 1995 Shyu 701/117), U.S. Pat. No. 6,473,688 (Kohno, et al., Oct. 29, 2002, Traffic information transmitting system, traffic information collecting and distributing system and traffic information collecting and distributing method), U.S. Pat. No. 6,304,758 (October, 2001, Iierbig et al., 701/117); U.S. Pat. No. 6,411,221 (January, 2002, Horber, 701/117); U.S. Pat. No. 6,384,739 (May, 2002, Robert, Jr., 701/117); U.S. Pat. No. 6,401,027 (June, 2002, Xa et al., 701/117); U.S. Pat. No. 6,411,889 (June, 2002, Mizunuma et al., 701/117), U.S. Pat. No. 6,359,571 (Endo, et al., Mar. 19, 2002, Broadcasting type information providing system and travel environment information collecting device); U.S. Pat. No. 6,338,011 (Furst, et al., Jan. 8, 2002, Method and apparatus for sharing vehicle telemetry data among a plurality of users over a communications network); U.S. Pat. No. 5,131,020 (July, 1992, Liebesny et al., 455/422); U.S. Pat. No. 5,164,904 (November, 1992, Sumner, 701/117); U.S. Pat. No. 5,539,645 (July, 1996, Mandhyan et al., 701/119); U.S. Pat. No. 5,594,779 (January, 1997, Goodman, 455/4); U.S. Pat. No. 5,689,252 (November, 1997, Ayanoglu et al., 340/991); U.S. Pat. No. 5,699,056 (December, 1997, Yoshida, 340/905); U.S. Pat. No. 5,864,305 (January, 1999, Rosenquist, 340/905); U.S. Pat. No. 5,889,473 (March, 1999, Wicks, 340/825); U.S. Pat. No. 5,919,246 (July, 1999, Waizmann et al., 701/209); U.S. Pat. No. 5,982,298 (November, 1999, Lappenbusch et al., 340/905); U.S. Pat. No. 4,860,216 (August, 1989, Linsenmayer, 342/159); U.S. Pat. No. 5,302,955 (April, 1994, Schutte et al., 342/59); U.S. Pat. No.5,809,437 (September, 1998, Breed, 701/29); U.S. Pat. No. 6,115,654 (September, 2000, Eid et al., 701/34); U.S. Pat. No. 6,173,159 (January, 2001, Wright et al., 455/66); and Japanese Patent Document Nos. JP 9-236650 (September, 1997); 10-84430 (March, 1998); 5-151496 (June, 1993); and 11-183184 (July, 1999), each of which is expressly incorporated herein by reference. See also: Martin E. Liggins, II, et al., “Distributed Fusion Architectures and Algorithms for Target Tracking”, Proceedings of the IEEE, vol. 85, No. 1, (XP-002166088) January, 1997, pp. 95-106.; D. M. Hosmer, “Data-Linked Associate Systems”, 1994 IEEE International Conference on Systems, Man, and Cybernetics. Humans, Information and Technology (Cat. No. 94CH3571-5), Proceedings of IEEE International Conference on Systems, Man and Cybernetics, San Antonio, Tex., vol.3, (XP-002166089) (1994), pp. 2075-2079.

[1527] One aspect of the invention provides a communications system, method and infrastructure. According to one preferred embodiment, an ad hoc, self organizing, cellular radio system (sometimes known as a “mesh network”) is provided. Advantageously, high gain antennas are employed, preferably electronically steerable antennas, to provide efficient communications and to increase communications bandwidth, both between nodes and for the system comprising a plurality of nodes communicating with each other. See, U.S. Pat. No. 6,507,739 (Gross, et al., Jan. 14, 2003), expressly incorporated herein by reference.

[1528] In general, time-critical, e.g., voice communications require tight routing to control communications latency. On the other hand, non-time critical communications generally are afforded more leeway in terms of communications pathways, including a number of “hops”, retransmission latency, and out-of-order packet communication tolerance, between the source and destination or fixed infrastructure, and quality of communication pathway. Further, it is possible to establish redundant pathways, especially where communications bandwidth is available, multiple paths possible, and no single available path meets the entire communications requirements or preferences.

[1529] Technologies for determining a position of a mobile device are also well known. Most popular are radio triangulation techniques, including artificial satellite and terrestrial transmitters or receivers, dead reckoning and inertial techniques. Advantageously, a satellite-based or augmented satellite system, although other suitable geolocation systems are applicable.

[1530] Navigation systems are also well known. These systems generally combine a position sensing technology with a geographic information system (GIS), e.g., a mapping database, to assist navigation functions. Systems which integrate GPS, GLONASS, LORAN or other positioning systems into vehicular guidance systems are well known, and indeed navigational purposes were prime motivators for the creation of these systems.

[1531] Environmental sensors are well known. For example, sensing technologies for temperature, weather, object proximity, location and identification, vehicular traffic and the like are well developed. In particular, known systems for analyzing vehicular traffic patterns include both stationary and mobile sensors, and networks thereof. Most often, such networks provide a stationary or centralized system for analyzing traffic information, which is then broadcast to vehicles.

[1532] Encryption technologies are well known and highly developed. These are generally classified as being symmetric key, for example the Data Encryption Standard (DES), and the more recent Advanced Encryption Standard (AES), in which the same key is used for encryption as decryption, and asymmetric key cryptography, in which different and complementary keys are used to encrypt and decrypt, in which the former and the latter are not derivable from each other (or one from the other) and therefore can be used for authentication and digital signatures. The use of asymmetric keys allows a so-called public key infrastructure, in which one of the keys is published, to allow communications to be directed to a possessor of a complementary key, and/or the identity of the sender of a message to be verified. Typical asymmetric encryption systems include the Rivest-Shamir-Adelman algorithm (RSA), the Diffie-Hellman algorithm (DH), elliptic curve encryption algorithms, and the so-called Pretty Good Privacy (PGP) algorithm.

[1533] One embodiment of the invention provides a system that analyzes both a risk and an associated reliability. Another embodiment of the invention communicates the risk and associated reliability in a manner for efficient human comprehension, especially in a distracting environment. See, U.S. Pat. Nos. 6,201,493; 5,977,884; 6,118,403; 5,982,325; 5,485,161; WO0077539, each of which is expressly incorporated herein by reference, and the Uniden GPSRD (see Uniden GPSRD User's Manual, expressly incorporated herein by reference). See, also U.S. Pat. Nos. 5,650,770; 5,450,329; 5,504,482; 5,504,491; 5,539,645; 5,929,753; 5,983,161; 6,084,510; 6,255,942; 6,225,901; 5,959,529; 5,752,976; 5,748,103; 5,720,770; 6,005,517; 5,805,055; 6,147,598; 5,687,215; 5,838,237; 6,044,257; 6,144,336; 6,285,867; 6,340,928; 6,356,822; 6,353,679 each of which is expressly incorporated herein by reference.

[1534] Statistical Analysis

[1535] It is understood that the below analysis and analytical tools, as well as those known in the art, may be used individually, in sub-combination, or in appropriate combination, to achieve the goals of the invention. These techniques may be implemented in dedicated or reprogrammable/general purpose hardware, and may be employed for low level processing of signals, such as in digital signal processors, within an operating system or dynamic linked libraries, or within application software. Likewise, these techniques may be applicable, for example, to low level data processing, system-level data processing, or user interface data processing.

[1536] A risk and reliability communication system may be useful, for example, to allow a user to evaluate a set of events in statistical context. Most indicators present data by means of a logical indicator or magnitude, as a single value. Scientific displays may provide a two-dimensional display of a distribution, but these typically require significant user focus to comprehend, especially where a multimodal distribution is represented. User displays of a magnitude or binary value typically do not provide any information about a likelihood of error. Thus, while a recent positive warning of the existence of an event may be a reliable indicator of the actual existence of the event, the failure to warn of an event does not necessarily mean that the event does not exist. Further, as events age, their reliability often decreases.

[1537] A Bayesian network is a representation of the probabilistic relationships among distinctions about the world. Each distinction, sometimes called a variable, can take on one of a mutually exclusive and exhaustive set of possible states. Associated with each variable in a Bayesian network is a set of probability distributions. Using conditional probability notation, the set of probability distributions for a variable can be denoted by p(x_i|π_i, χ), where “p” refers to the probability distribution, where “π_i” denotes the parents of variable X_i and where “χ” denotes the knowledge of the expert. The Greek letter “χ” indicates that the Bayesian network reflects the knowledge of an expert in a given field. Thus, this expression reads as follows: the probability distribution for variable X_i given the parents of X_i and the knowledge of the expert. For example, X₁ is the parent of X₂. The probability distributions specify the strength of the relationships between variables. For instance, if X₁ has two states (true and false), then associated with X₁ is a single probability distribution p(x₁|χ)p and associated with X₂ are two probability distributions p(x_i|X₁=t,χ) and p(X₂|X₁=f,χ).

[1538] A Bayesian network is expressed as an acyclic-directed graph where the variables correspond to nodes and the relationships between the nodes correspond to arcs. The arcs in a Bayesian network convey dependence between nodes. When there is an arc between two nodes, the probability distribution of the first node depends upon the value of the second node when the direction of the arc points from the second node to the first node. Missing arcs in a Bayesian network convey conditional independencies. However, two variables indirectly connected through intermediate variables are conditionally dependent given lack of knowledge of the values (“states”) of the intermediate variables. In other words, sets of variables X and Y are said to be conditionally independent, given a set of variables Z, if the probability distribution for X given Z does not depend on Y. If Z is empty, however, X and Y are said to be “independent” as opposed to conditionally independent. If X and Y are not conditionally independent, given Z, then X and Y are said to be conditionally dependent given Z.

[1539] The variables used for each node may be of different types. Specifically, variables may be of two types: discrete or continuous. A discrete variable is a variable that has a finite or countable number of states, whereas a continuous variable is a variable that has an effectively infinite number of states. An example of a discrete variable is a Boolean variable. Such a variable can assume only one of two states: “true” or “false.” An example of a continuous variable is a variable that may assume any real value between −1 and 1. Discrete variables have an associated probability distribution. Continuous variables, however, have an associated probability density function (“density”). Where an event is a set of possible outcomes, the density p(x) for a variable “x” and events “a” and “b” is defined as:

[1540] $p\left(x\right)=\underset{a\to b}{\mathrm{Lim}}\left[\frac{p\left(a\le x\le b\right)}{(a-b}\right]$

[1541] where p(a≦x≦b) is the probability that x lies between a and b. Conventional systems for generating Bayesian networks cannot use continuous variables in their nodes.

[1542] There are two conventional approaches for constructing Bayesian networks. Using the first approach (“the knowledge-based approach”), first the distinctions of the world that are important for decision making are determined. These distinctions correspond to the variables of the domain of the Bayesian network. The “domain” of a Bayesian network is the set of all variables in the Bayesian network. Next the dependencies among the variables (the arcs) and the probability distributions that quantify the strengths of the dependencies are determined.

[1543] In the second approach (“called the data-based approach”), the variables of the domain are first determined. Next, data is accumulated for those variables, and an algorithm is applied that creates a Bayesian network from this data. The accumulated data comes from real world instances of the domain. That is, real world instances of decision making in a given field. Conventionally, this second approach exists for domains containing only discrete variables.

[1544] U.S. application Ser. No. 08/240,019 filed May 9, 1994 entitled “Generating Improved Belief Networks” describes a system and method for generating Bayesian networks (also known as “belief networks”) that utilize both expert data received from an expert (“expert knowledge”) and data received from real world instances of decisions made (“empirical data”). By utilizing both expert knowledge and empirical data, the network generator provides an improved Bayesian network that may be more accurate than conventional Bayesian networks or provide other advantages, e.g., ease of implementation and lower reliance on “expert” estimations of probabilities. Likewise, it is known to initiate a network using estimations of the probabilities (and often the relevant variables), and subsequently use accumulated data to refine the network to increase its accuracy and precision.

[1545] Expert knowledge consists of two components: an equivalent sample size or sizes (“sample size”), and the prior probabilities of all possible Bayesian-network structures (“priors on structures”). The effective sample size is the effective number of times that the expert has rendered a specific decision. For example, a doctor with 20 years of experience diagnosing a specific illness may have an effective sample size in the hundreds. The priors on structures refers to the confidence of the expert that there is a relationship between variables (e.g., the expert is 70% sure that two variables are related). The priors on structures can be decomposed for each variable-parent pair known as the “prior probability” of the variable-parent pair. Empirical data is typically stored in a database. The database may contain a list of the observed state of some or all of the variables in the Bayesian network. Each data entry constitutes a case. When one or more variables are unobserved in a case, the case containing the unobserved variable is said to have “missing data.” Thus, missing data refers to when there are cases in the empirical data database that contain no observed value for one or more of the variables in the domain. An assignment of one state to each variable in a set of variables is called an “instance” of that set of variables. Thus, a “case” is an instance of the domain. The “database” is the collection of all cases.

[1546] Therefore, it is seen that Bayesian networks can be used to probabilistically model a problem, in a mathematical form. This model may then be analyzed to produce one or more outputs representative of the probability that a given fact is true, or a probability density distribution that a variable is at a certain value.

[1547] A review of certain statistical methods is provided below for the convenience of the reader, and is not intended to limit the scope of methods, of statistical of other type, which may be employed in conjunction with the system and method according to the present invention. It is understood that these mathematical models and methods may be implemented in known manner on general purpose computing platforms, for example as a compiled application in a real-time operating system such as RT Linux, QNX, versions of Microsoft Windows, or the like. Further, these techniques may be implemented as applets operating under Matlab or other scientific computing platform. Alternately, the functions may be implemented natively in an embedded control system or on a microcontroller.

[1548] It is also understood that, while the mathematical methods are capable of producing precise and accurate results, various simplyfying presumptions and truncations may be employed to increase the tractability of the problem to be solved. Further, the outputs generally provided according to preferred embodiments of the present invention are relatively low precision, and therefore higher order approximation of the analytic solution, in the case of a rapidly convergent calculation, will often be sufficient.

[1549] A time domain process demonstrates a Markov property if the conditional probability density of the current event, given all present and past events, depends only on the jth most recent events. If the current event depends solely on the most recent past event, then the process is a first order Markov process. There are three key problems in HMM use: evaluation, estimation, and decoding. The evaluation problem is that given an observation sequence and a model, what is the probability that the observed sequence was generated by the model (Pr(O|λ)) If this can be evaluated for all competing models for an observation sequence, then the model with the highest probability can be chosen for recognition.

[1550] Pr(O|λ) can be calculated several ways. The naive way is to sum the probability over all the possible state sequences in a model for the observation sequence:

[1551] $\mathrm{Pr}(O\lambda )=\sum _{\mathrm{all}S}\prod _{i=1}^T{a}_{b_{t-1}\mathrm{ag}}{b}_{\mathrm{bc}}\left(O_k\right)$

[1552] However, this method is exponential in time, so the more efficient forward-backward algorithm is used in practice. The following algorithm defines the forward variable a and uses it to generate Pr(O|λ)(π are the initial state probabilities, a are the state transition probabilities, and b are the output probabilites).

• • [1553] a₁(i)=π_ib_i(O₁), for all states i

[1554] $(\mathrm{if}i\in S_I,{\pi }_i=\frac{1}{n_f};$
otherwise π_i=[ ])

• • [1555] Calculating a( ) along the time axis, for t=2, . . . I, and all states j, compute

[1556] $a_t\left(j\right)=\left[\sum _i{a}_{i-1}\left(i\right)a_{\mathrm{ij}}\right]b_j\left(O_k\right)$

• • [1557] Final probability is given by

[1558] $\mathrm{Pr}(O\lambda )=\sum _{i\in S_p}{a}_T\left(i\right)$

[1559] The first step initializes the forward variable with the initial probability for all states, while the second step inductively steps the forward variable through time. The final step gives the desired result Pr(O|λ) and it can be shown by constructing a lattice of states and transitions through time that the computation is only order O(N²T). The backward algorithm, using a process similar to the above, can also be used to compute Pr(O|λ) and defines the convenience variable β.

[1560] The estimation problem concerns how to adjust λto maximize Pr(O|λ) given an observation sequence O. Given an initial model, which can have flat probabilities, the forward-backward algorithm allows us to evaluate this probability. All that remains is to find a method to improve the initial model. Unfortunately, an analytical solution is not known, but an iterative technique can be employed.

[1561] Using the actual evidence from the training data, a new estimate for the respective output probability can be assigned:

[1562] ${\stackrel{\_}{b}}_j\left(k\right)=\frac{\sum _{i\in O_t=u_k}{\gamma }_b\left(j\right)}{\sum _{t=1}^T{\gamma }_b\left(j\right)}$

[1563] where γ_i(i) is defined as the posterior probability of being in state i at time t given the observation sequence and the model. Similarly, the evidence can be used to develop a new estimate of the probability of a state transition (ā_ij) and initial state probabilities ( π_i).

[1564] Thus all the components of model ( λ) can be re-estimated. Since either the forward or backward algorithm can be used to evaluate Pr(O | λ) versus the previous estimation, the above technique can be used iteratively to converge the model to some limit. While the technique described only handles a single observation sequence, it is easy to extend to a set of observation sequences.

[1565] The Hidden Markov Model is a finite set of states, each of which is associated with a (generally multidimensional) probability distribution. Transitions among the states are governed by a set of probabilities called transition probabilities. In a particular state an outcome or observation can be generated, according to the associated probability distribution. It is only the outcome, not the state visible to an external observer and therefore states are “hidden” to the outside; hence the name Hidden Markov Model.

[1566] In order to define an HMM completely, following elements are needed.

• • [1567] The number of states of the model, N.
  • [1568] The number of observation symbols in the alphabet, M. If the observations are continuous then M is infinite.
  • [1569] A set of state transition probabilities Λ={a_ij}
    a_ij=p{q_t+1=j|q_t=i}, 1≦i,j ≦N,
  • [1570] where q_t denotes the current state.

[1571] Transition probabilities should satisfy the normal stochastic constraints,

[1572] $a_{\mathrm{ij}}\ge 0,1\le i,j\le N$ $\mathrm{and}$ $\sum _{j=1}^N{a}_{\mathrm{ij}}=1,1\le i\le N$

• • [1573] A probability distribution in each of the states, B={b_j(k)}
    b_j(k)=p{o_t=v_k|q_t=j}, 1≦j≦N, 1≦k≦M

[1574] where v_kdenotes the k^thobservation symbol in the alphabet, and o_tthe current parameter vector.

[1575] Following stochastic constraints must be satisfied.

[1576] $b_j\left(k\right)\ge 0,1\le j\le N,1\le k\le M$ $\mathrm{and}$ $\sum _{k=1}^M{b}_j\left(k\right)=1,1\le j\le N$

[1577] If the observations are continuous then we will have to use a continuous probability density function, instead of a set of discrete probabilities. In this case we specify the parameters of the probability density function. Usually the probability density is approximated by a weighted sum of M Gaussian distributions N,

[1578] $b_j\left(a_t\right)=\sum _{m=1}^M{c}_{\mathrm{jm}}𝒩\left({\mu }_{\mathrm{jm}},\sum _{\mathrm{jm}},a_t\right)$

[1579] where,

• • [1580] c_jm=weighting coefficients
  • [1581] μ_jm=mean vectors
  • [1582] Σ_jm=Covariance matrices

[1583] c_jm should satisfy the stochastic constrains,
c_jm≧0, 1≦j≦N, 1≦m≦M

[1584] and

[1585] $\sum _{m=1}^M{c}_{\mathrm{jm}}=1,1\le j\le N$ $\pi =\left\{{\pi }_i\right\}.$

• • [1586] The initial state distribution,
    where,
    π_i=p{q₁=i}, 1≦i≦N
    Therefore we can use the compact notation
    λ=(A, B, π)
    to denote an HMM with discrete probability distributions, while
    λ=(A, c_jm,μ_jm, Σ_jm, π)
    to denote one with continuous densities.

[1587] For the sake of mathematical and computational tractability, following assumptions are made in the theory of HMMs.

[1588] (1) The Markov Assumption

[1589] As given in the definition of HMMs, transition probabilities are defined as,
a_ij=p{q_t+1=j|q_t=i}.

[1590] In other words it is assumed that the next state is dependent only upon the current state. This is called the Markov assumption and the resulting model becomes actually a first order HMM.

[1591] However generally the next state may depend on past k states and it is possible to obtain a such model, called an k^th order HMM by defining the transition probabilities as follows.
a_{i1i2. . . ikj}=p{q_t+1=j|q_t=i₁, q_t−1=i₂, . . . , q_t−k+1=i_k}, 1≦i₁, i₂, . . . , i_k,j≦N.

[1592] But it is seen that a higher order HMM will have a higher complexity. Even though the first order HMMs are the most common, some attempts have been made to use the higher order HMMs too.

[1593] (2) The Stationarity Assumption

[1594] Here it is assumed that state transition probabilities are independent of the actual time at which the transitions takes place. Mathematically,
p{q_t1+1=j|q_t1=i}=p{q_t2+1=j|q_t2=i},
for any t₁ and t₂.

[1595] (3) The Output Independence Assumption

[1596] This is the assumption that current output(observation) is statistically independent of the previous outputs(observations). We can formulate this assumption mathematically, by considering a sequence of observations,
O=o₁,o₂, . . . , o_T.

[1597] Then according to the assumption for an HMM λ,

[1598] $p\left\{O|q_1,q_2,\dots ,q_T,\lambda \right\}=\prod _{t=1}^{T}p\left(o_t|q_t,\lambda \right).$

[1599] However unlike the other two, this assumption has a very limited validity. In some cases this assumption may not be fair enough and therefore becomes a severe weakness of the HMMs.

[1600] A Hidden Markov Model (HMM) is a Markov chain, where each state generates an observation. You only see the observations, and the goal is to infer the hidden state sequence. HMMs are very useful for time-series modeling, since the discrete state-space can be used to approximate many non-linear, non-Gaussian systems.

[1601] HMMs and some common variants (e.g., input-output HMMs) can be concisely explained using the language of Bayesian Networks, as we now demonstrate.

[1602] Consider the Bayesian network in FIG. 1, which represents a hidden Markov model (HMM). (Circles denote continuous-valued random variables, squares denote discrete-valued, clear means hidden, shaded means observed.) This encodes the joint distribution
P(Q,Y)=P(Q₁) P(Y₁|Q₁) P(Q₂|Q₁) P(Y₂|Q₂)

[1603] For a sequence of length T, we simply “unroll” the model for T time steps. In general, such a dynamic Bayesian network (DBN) can be specified by just drawing two time slices (this is sometimes called a 2TBN)—the structure (and parameters) are assumed to repeat.

[1604] The Markov property states that the future is independent of the past given the present, i.e., Q_{t+1}\indep Q_{t−1}|Q_t. We can parameterize this Markov chain using a transition matrix, M_{ij}=P(Q_{t+1}=j|Q_t=i), and a prior distribution, π_i=P(Q₁=i).

[1605] We have assumed that this is a homogeneous Markov chain, i.e., the parameters do not vary with time. This assumption can be made explicit by representing the parameters as nodes: see FIG. 2: P1 represents π, P2 represents the transition matrix, and P3 represents the parameters for the observation model. If we think of these parameters as random variables (as in the Bayesian approach), parameter estimation becomes equivalent to inference. If we think of the parameters as fixed, but unknown, quantities, parameter estimation requires a separate learning procedure (usually EM). In the latter case, we typically do not represent the parameters in the graph; shared parameters (as in this example) are implemented by specifying that the corresponding CPDs are “tied”.

[1606] An HMM is a hidden Markov model because we don't see the states of the Markov chain, Q_t, but just a function of them, namely Y_t. For example, if Y_t is a vector, we might define P(Y_t=y|Q_t=i)=N(y; μ_i, σ_i). A richer model, widely used in speech recognition, is to model the output (conditioned on the hidden state) as a mixture of Gaussians. This is shown in FIG. 3.

[1607] Some popular variations on the basic HMM theme are illustrated in FIGS. 4A, 4B and 4C, which represent, respectively, an input-output HMM, a factorial HMM, and a coupled HMM. (In the input-output model, the CPD P(Q|U) could be a softmax function, or a neural network.) Software is available to handle inference and learning in general Bayesian networks, making all of these models trivial to implement.

[1608] It is noted that the parameters may also vary with time. This does not violate the presumptions inherent in an HMM, but rather merely complicates the analysis since a static simplifying presumption may not be made.

[1609] A discrete-time, discrete-space dynamical system governed by a Markov chain emits a sequence of observable outputs: one output (observation) for each state in a trajectory of such states. From the observable sequence of outputs, we may infer the most likely dynamical system. The result is a model for the underlying process. Alternatively, given a sequence of outputs, we can infer the most likely sequence of states. We might also use the model to predict the next observation or more generally a continuation of the sequence of observations.

[1610] The Evaluation Problem and the Forward Algorithm

[1611] We have a model λ=(A, B, π) and a sequence of observations O=o₁, o₂, . . . , o_T, and p{O|λ}must be found. We can calculate this quantity using simple probabilistic arguments. But this calculation involves number of operations in the order of N^T. This is very large even if the length of the sequence, T is moderate. Therefore we have to look for an other method for this calculation. Fortunately there exists one which has a considerably low complexity and makes use an auxiliary variable, a_t(i) called forward variable.

[1612] The forward variable is defined as the probability of the partial observation sequence o₁,o₂, . . . , o_T, when it terminates at the state i. Mathematically,
a_t(i)=p{o₁, o₂, . . . , o_t, q_t=i|λ}  (1.1)

[1613] Then it is easy to see that following recursive relationship holds.

[1614] $\begin{array}{cc}{\alpha }_{t+1}\left(j\right)=b_j\left(o_{t+1}\right)\sum _{i=1}^N{\alpha }_t\left(i\right)a_{\mathrm{ij}},1\le j\le N,1\le t\le T-1& \left(1.2\right)\end{array}$

[1615] where,
a₁(j)=π_jb_j(o₁), 1≦j≦N

[1616] Using this recursion we can calculate
a_T(i)=1≦i≦N

[1617] and then the required probability is given by,

[1618] $\begin{array}{cc}p\left\{O|\lambda \right\}=\sum _{i=1}^N{\alpha }_T\left(i\right).& \left(1.3\right)\end{array}$

[1619] The complexity of this method, known as the forward algorithm is proportional to N²T, which is linear with respect to T whereas the direct calculation mentioned earlier, had an exponential complexity.

[1620] In a similar way we can define the backward variable β_t(i) as the probability of the partial observation sequence o_t+1, o_t+2 , . . . , o_T, given that the current state is i. Mathematically,
β_t(i)=p{o_t+1, o_t+2, . . . , o_T|q_t=i, λ}  (1.4)

[1621] As in the case of a_t(i) there is a recursive relationship which can be used to calculate β_t(i) efficiently.

[1622] $\begin{array}{cc}{\beta }_t\left(i\right)=\sum _{j=1}^N{\beta }_{t+1}\left(j\right)a_{\mathrm{ij}}{b}_j\left(o_{t+1}\right),1\le i\le N,1\le t\le T-1& \left(1.5\right)\end{array}$

[1623] where,
β_T(i)=1, 1≦i≦N

[1624] Further we can see that,
a_t(i)β_t(i)=p{O, q_t=i|λ}, 1≦i≦N, 1≦t≦T   (1.6)

[1625] Therefore this gives another way to calculate p{O|λ}, by using both forward and backward variables as given in eqn. 1.7. See, http://jedlik.phy.bme.hu/˜gerjanos/HMM/, expressly incorporated herein by reference.

[1626] $\begin{array}{cc}p\left\{O|\lambda \right\}=\sum _{i=1}^{N}p\left\{O,q_t=i|\lambda \right\}=\sum _{i=1}^N{\alpha }_t\left(i\right){\beta }_t\left(i\right)& \left(1.7\right)\end{array}$

[1627] Eqn. 1.7 is very useful, specially in deriving the formulas required for gradient based training.

[1628] The Decoding Problem and the Viterbi Algorithm

[1629] While the estimation and evaluation processes described above are sufficient for the development of an HMM system, the Viterbi algorithm provides a quick means of evaluating a set of HMM's in practice as well as providing a solution for the decoding problem. In decoding, the goal is to recover the state sequence given an observation sequence. The Viterbi algorithm can be viewed as a special form of the forward-backward algorithm where only the maximum path at each time step is taken instead of all paths. This optimization reduces computational load and allows the recovery of the most likely state sequence. The steps to the Viterbi are

• • [1630] Initialization. For all states i, δ₁(i)=π_ib_i(O₁);ψ_i(i)=[ ]
  • [1631] Recursion. From t=2 to T and for all states j, b₁(j)=Max_i[b_i−1(i)a_ij]b_j(O₁);ψ₁(j)=argmax_i[δ_i−1(i)a_ij]
  • [1632] Termination. P=Max[δ_T(s)],s_T=argmax[δ_T(s)]
  • [1633] Recovering the state sequence. From t=T−1 to 1, s_i=ψ_i+1(s_i+1)

[1634] In many HMM system implementations, the Viterbi algorithm is used for evaluation at recognition time. Note that since Viterbi only guarantees the maximum of Pr(O,S|λ) over all state sequences S (as a result of the first order Markov assumption) instead of the sum over all possible state sequences, the resultant scores are only an approximation.

[1635] So far the discussion has assumed some method of quantization of feature vectors into classes. However, instead of using vector quantization, the actual probability densities for the features may be used. Baum-Welch, Viterbi, and the forward-backward algorithms can be modified to handle a variety of characteristic densities. In this context, however, the densities will be assumed to be Gaussian. Specifically,

[1636] $b_j\left(O_t\right)=\frac{1}{\sqrt{{\left(2\pi \right)}^n{\sigma }_j}}{e}^{\frac{1}{2}{\left(O_t-{\mu }_j\right)}^{\prime }{\sigma }_j^{-1}\left(O_t-{\mu }_j\right)}$

[1637] Initial estimations of μ and σ may be calculated by dividing the evidence evenly among the states of the model and calculating the mean and variance in the normal way. Whereas flat densities were used for the initialization step before, the evidence is used here. Now all that is needed is a way to provide new estimates for the output probability. We wish to weight the influence of a particular observation for each state based on the likelihood of that observation occurring in that state. Adapting the solution from the discrete case yields

[1638] ${\stackrel{\_}{\mu }}_j=\frac{\sum _{t=1}^T{\gamma }_t\left(j\right)O_t}{\sum _{t=1}^T{\gamma }_t\left(j\right)}$ $\mathrm{and}$ ${\stackrel{\_}{\sigma }}_j=\frac{\sum _{t=1}^T{\gamma }_t\left(j\right)\left(O_t-{\stackrel{\_}{\mu }}_j\right){\left(O_t-{\stackrel{\_}{\mu }}_j\right)}^t}{\sum _{t=1}^T{\gamma }_t\left(j\right)}$

[1639] For convenience, μ_j is used to calculate σ_j instead of the re-estimated μ_j. While this is not strictly proper, the values are approximately equal in contiguous iterations and seem not to make an empirical difference. See, http://www.white.media.mit.edu/˜testarne/asl/asl-tr375, expressly incorporated herein by reference. Since only one stream of data is being used and only one mixture (Gaussian density) is being assumed, the algorithms above can proceed normally, incorporating these changes for the continuous density case.

[1640] We want to find the most likely state sequence for a given sequence of observations, O=o₁, o₂, . . . , o_T and a model, λ=(A, B, π).

[1641] The solution to this problem depends upon the way “most likely state sequence” is defined. One approach is to find the most likely state q_tat t=t and to concatenate all such ‘q_t’s. But sometimes, this method does not give a physically meaningful state sequence. Therefore we would seek another method which has no such problems. In this method, commonly known as Viterbi algorithm, the whole state sequence with the maximum likelihood is found. In order to facilitate the computation we define an auxiliary variable,

[1642] ${\delta }_t\left(i\right)=\underset{q_1{q}_2\dots q_{t-1}}{\max }p\left\{q_1,q_2,\dots ,q_{t-1},q_t=i,o_1,o_2,\dots ,o_{t-1}|\lambda \right\},$

[1643] which gives the highest probability that partial observation sequence and state sequence up to t=t can have, when the current state is i.

It is easy to observe that the following recursive relationship holds.

[1644] $\begin{array}{cc}{\delta }_{t+1}\left(j\right)=b_j\left(o_{t+1}\right)\left[\underset{1\le i\le N}{\max }{\delta }_t\left(i\right)a_{\mathrm{ij}}\right],1\le i\le N,1\le t\le T-1& \left(1.8\right)\end{array}$

[1645] where,
δ₁(j)=π_jb_j(o₁), 1≦j≦N

[1646] So the procedure to find the most likely state sequence starts from calculation of δ_T(j), 1≦j≦N using recursion in 1.8, while always keeping a pointer to the “winning state” in the maximum finding operation. Finally the state j*, is found where

[1647] $j^{*}=\arg \underset{1\le j\le N}{\max }{\delta }_T\left(j\right),$

[1648] and starting from this state, the sequence of states is back-tracked as the pointer in each state indicates.This gives the required set of states.

[1649] This whole algorithm can be interpreted as a search in a graph whose nodes are formed by the states of the HMM in each of the time instant t, 1≦t≦T.

[1650] The Learning Problem

[1651] Generally, the learning problem is how to adjust the HMM parameters, so that the given set of observations (called the training set) is represented by the model in the best way for the intended application. Thus it would be clear that the “quantity” we wish to optimize during the learning process can be different from application to application. In other words there may be several optimization criteria for learning, out of which a suitable one is selected depending on the application.

[1652] There are two main optimization criteria found in ASR literature; Maximum Likelihood (ML) and Maximum Mutual Information (MMI). The solutions to the learning problem under each of those criteria is described below.

[1653] Maximum Likelihood (ML) Criterion

[1654] In ML we try to maximize the probability of a given sequence of observations O^W, belonging to a given class w, given the HMM λ_w of the class w, with respect to the parameters of the model λ_w. This probability is the total likelihood of the observations and can be expressed mathematically as
L_tot=p{O^W|λ_w}

[1655] However since we consider only one class w at a time we can drop the subscript and superscript ‘w’s. Then the ML criterion can be given as,
L_tot=p{O|λ}  (1.9)

[1656] However there is no known way to analytically solve for the model λ=(Λ, B, π), which maximize the quantity L_tot. But we can choose model parameters such that it is locally maximized, using an iterative procedure, like Baum-Welch method or a gradient based method, which are described below.

[1657] Baum-Welch Algorithm

[1658] This method can be derived using simple “occurrence counting” arguments or using calculus to maximize the auxiliary quantity

[1659] $Q\left(\lambda ,\stackrel{\_}{\lambda }\right)=\sum _{q}p\left\{q|O,\lambda \right\}\log \left[p\left\{O,q,\stackrel{\_}{\lambda }\right\}\right]$

[1660] over λ[ ],[, p 344-346,]. A special feature of the algorithm is the guaranteed convergence.

[1661] To describe the Baum-Welch algorithm, (also known as Forward-Backward algorithm), we need to define two more auxiliary variables, in addition to the forward and backward variables defined in a previous section. These variables can however be expressed in terms of the forward and backward variables.

[1662] First one of those variables is defined as the probability of being in state i at t=t and in state j at t=t+1. Formally,
ξ_t(i, j)=p{q_t=i, q_t+1=j|O, λ}  (1.10)

[1663] This is the same as,

[1664] $\begin{array}{cc}{\xi }_t\left(i,j\right)=\frac{p\left\{q_t=i,q_{t+1}=j,O|\lambda \right\}}{p\left\{O|\lambda \right\}}& \left(1.11\right)\end{array}$

[1665] Using forward and backward variables this can be expressed as,

[1666] $\begin{array}{cc}{\xi }_t\left(i,j\right)=\frac{{\alpha }_t\left(i\right)a_{\mathrm{ij}}{\beta }_{t+1}\left(j\right)b_j\left(o_{t+1}\right)}{\sum _{i=1}^N\sum _{j=1}^N{\alpha }_t\left(i\right)a_{\mathrm{ij}}{\beta }_{t+1}\left(j\right)b_j\left(o_{t+1}\right)}& \left(1.12\right)\end{array}$

[1667] The second variable is the a posteriori probability,
γ_t(i)=p{q_t=i|O, λ}  (1.13)

[1668] that is the probability of being in state i at t=t, given the observation sequence and the model. In forward and backward variables this can be expressed by,

[1669] $\begin{array}{cc}{\gamma }_t\left(i\right)=\left[\frac{{\alpha }_t\left(i\right){\beta }_t\left(i\right)}{\sum _{i=1}^N{\alpha }_t\left(i\right){\beta }_t\left(i\right)}\right]& \left(1.14\right)\end{array}$

[1670] One can see that the relationship between γ_t(i) and ξ_t(i, j) is given by,

[1671] $\begin{array}{cc}{\gamma }_t\left(i\right)=\sum _{j=1}^N{\xi }_t\left(i,j\right),1\le i\le N,1\le t\le M& \left(1.15\right)\end{array}$

[1672] Now it is possible to describe the Baum-Welch learning process, where parameters of the HMM is updated in such a way to maximize the quantity, p{O|λ}. Assuming a starting model λ=(A, B, π), we calculate the ‘α’s and ‘β’s using the recursions 1.5 and 1.2, and then ‘ξ’s and ‘γ’s using 1.12 and 1.15. Next step is to update the HMM parameters according to eqns 1.16 to 1.18, known as re-estimation formulas.

[1673] $\begin{array}{cc}{\stackrel{\_}{\pi }}_i={\gamma }_1\left(i\right),1\le i\le N& \left(1.16\right)\\ {\stackrel{\_}{a}}_{\mathrm{ij}}=\frac{\sum _{t=1}^{T-1}{\xi }_t\left(i,j\right)}{\sum _{t=1}^{T-1}{\gamma }_t\left(i\right)},1\le i\le N,1\le j\le N& \left(1.17\right)\\ {\stackrel{\_}{b}}_j\left(k\right)=\frac{\sum _{\underset{o_t=v_k}{t=1}}^T{\gamma }_t\left(j\right)}{\sum _{t=1}^T{\gamma }_t\left(j\right)},1\le j\le N,1\le k\le M& \left(1.18\right)\end{array}$

[1674] These reestimation formulas can easily be modified to deal with the continuous density case too.

[1675] Gradient Based Method

[1676] In the gradient based method, any parameter Θ of the HMM λ is updated according to the standard formula,

[1677] $\begin{array}{cc}{\Theta }^{\mathrm{new}}={\Theta }^{\mathrm{old}}-{\eta \left[\frac{\partial J}{\partial \Theta }\right]}_{\Theta ={\Theta }_{\mathrm{old}}}& \left(1.19\right)\end{array}$

[1678] where J is a quantity to be minimized. We define in this case,
J=E_ML=−log(p{O|λ})=−log(L_tot)   (1.20)

[1679] Since the minimization of J=E_ML is equivalent to the maximization of L_tot, eqn. 1.19 yields the required optimization criterion, ML. But the problem is to find the derivative

[1680] $\frac{\partial J}{\partial \Theta }$
for any parameter Θ of the model. This can be easily done by relating J to model parameters via L_tot. As a key step to do so, using the eqns. 1.7 and 1.9 we can obtain,

[1681] $\begin{array}{cc}{L}_{\mathrm{tot}}=\sum _{i=1}^{N}p\left\{O,q_t=i|\lambda \right\}=\sum _{i=1}^N{\alpha }_t\left(i\right){\beta }_t\left(i\right)& \left(1.21\right)\end{array}$

[1682] Differentiating the last equality in eqn. 1.20 with respect to an arbitrary parameter Θ,

[1683] $\begin{array}{cc}\frac{\partial J}{\partial \Theta }=-\frac{1}{L_{\mathrm{tot}}}\frac{\partial L_{\mathrm{tot}}}{\partial \Theta }& \left(1.22\right)\end{array}$

[1684] Eqn. 1.22 gives

[1685] $\frac{\partial J}{\partial \Theta },$
if we know

[1686] $\frac{\partial L_{\mathrm{tot}}}{\partial \Theta }$
which can be found using eqn. 1.21. However this derivative is specific to the actual parameter concerned. Since there are two main parameter sets in the HMM, namely transition probabilities a_ij, 1≦i, j≦N and observation probabilities b_j(k), 1≦j≦N, 1≦k≦M, we can find the derivative

[1687] $\frac{\partial L_{\mathrm{tot}}}{\partial \Theta }$
for each of the parameter sets and hence the gradient,

[1688] $\frac{\partial J}{\partial \Theta }.$

[1689] Gradient With Respect to Transition Probabilities

[1690] Using the chain rule,

[1691] $\begin{array}{cc}\frac{\partial L_{\mathrm{tot}}}{\partial a_{\mathrm{ij}}}=\sum _{t=1}^T\frac{\partial L_{\mathrm{tot}}}{\partial {\alpha }_t\left(j\right)}\frac{\partial {\alpha }_t\left(j\right)}{\partial a_{\mathrm{ij}}}& \left(1.23\right)\end{array}$

[1692] By differentiating eqn. 1.21 with respect to α_t(j) we get,

[1693] $\begin{array}{cc}\frac{\partial L_{\mathrm{tot}}}{\partial {\alpha }_t\left(j\right)}={\beta }_t\left(j\right),& \left(1.24\right)\end{array}$

[1694] and differentiating (a time shifted version of) eqn 1.2 with respect to a_ij

[1695] $\begin{array}{cc}\frac{\partial {\alpha }_t\left(j\right)}{\partial a_{\mathrm{ij}}}=b_j\left(o_t\right){\alpha }_{t-1}\left(i\right)& \left(1.25\right)\end{array}$

[1696] Eqns. 1.23, 1.24 and 1.25 give,

[1697] $\frac{\partial L_{\mathrm{tot}}}{\partial a_{\mathrm{ij}}},$
and substituting this quantity in eqn.1.22 (keeping in mind that Θ=a_ij in this case), we get the required result,

[1698] $\begin{array}{cc}\frac{\partial J}{\partial a_{\mathrm{ij}}}=-\frac{1}{L_{\mathrm{tot}}}\sum _{t=1}^T{\beta }_t\left(j\right)b_j\left(o_t\right){\alpha }_{t-1}\left(i\right)& \left(1.26\right)\end{array}$

[1699] Gradient With Respect to Observation Probabilities

[1700] Using the chain rule,

[1701] $\begin{array}{cc}\frac{\partial L_{\mathrm{tot}}}{\partial b_j\left(a_t\right)}=\frac{\partial L_{\mathrm{tot}}}{\partial {\alpha }_t\left(j\right)}\frac{\partial {\alpha }_t\left(j\right)}{\partial b_j\left(a_t\right)}& \left(1.27\right)\end{array}$

[1702] Differentiating (a time shifted version of) the eqn.1.2 with respect to b_j(O_t)

[1703] $\begin{array}{cc}\frac{\partial {\alpha }_t\left(j\right)}{\partial b_j\left(a_t\right)}=\frac{{\alpha }_t\left(j\right)}{b_j\left(a_t\right)}& \left(1.28\right)\end{array}$

[1704] Finally we get the required probability, by substituting for

[1705] $\frac{\partial L_{\mathrm{tot}}}{\partial b_j\left(O_t\right)}$
in eqn. 1.22 (keeping in mind that Θ=b_j(o_t) in this case), which is obtained by substituting eqns.1.28 and 1.24 in eqn.1.27.

[1706] $\begin{array}{cc}\frac{\partial J}{\partial b_j\left(a_t\right)}=-\frac{1}{L_{\mathrm{tot}}}\frac{{\alpha }_t\left(h\right){\beta }_t\left(j\right)}{b_j\left(a_t\right)},& \left(1.29\right)\end{array}$

[1707] Usually this is given the following form, by first substituting for L_tot from eqn.1.21 and then substituting from eqn.1.14.

[1708] $\begin{array}{cc}\frac{\partial J}{\partial b_j\left(a_t\right)}=-\frac{{\gamma }_t\left(j\right)}{b_j\left(a_t\right)},& \left(1.30\right)\end{array}$

[1709] If the continuous densities are used then

[1710] $\frac{\partial J}{\partial c_{\mathrm{jm}}},\frac{\partial J}{\partial \mathrm{\mu j}m}\mathrm{and}\frac{\partial J}{\partial \Sigma \mathrm{jm}}$
can be found by further propagating the derivative

[1711] $\frac{\partial J}{\partial b_j\left(O_t\right)}$
using the chain rule.
The same method can be used to propagate the derivative (if necessary) to a front end processor of the HMM. This will be discussed in detail later.

[1712] Maximum Mutual Information (MMI) Criterion

[1713] In ML we optimize an HMM of only one class at a time, and do not touch the HMMs for other classes at that time. This procedure does not involve the concept “discrimination” which is of great interest in Pattern Recognition. Thus the ML learning procedure gives a poor discrimination ability to the HMM system, specially when the estimated parameters (in the training phase) of the HMM system do not match with the inputs used in the recognition phase. This type of mismatches can arise due to two reasons. One is that the training and recognition data may have considerably different statistical properties, and the other is the difficulties of obtaining reliable parameter estimates in the training.

[1714] The MMI criterion on the other hand consider HMMs of all the classes simultaneously, during training. Parameters of the correct model are updated to enhance it's contribution to the observations, while parameters of the alternative models are updated to reduce their contributions. This procedure gives a high discriminative ability to the system and thus MMI belongs to the so called “discriminative training” category.

[1715] In order to have a closer look at the MMI criterion, consider a set of HMMs
A={λ_v, 1≦v≦V }.

[1716] The task is to minimize the conditional uncertainty of a class v of utterances given an observation sequence O^ of that class. This is equivalent minimize the conditional information,
I(v|O{circumflex over (0)}, A)=−log p{v|O{circumflex over (0)}, A}  (1.31)

[1717] with respect to A.

[1718] In an information theoretical frame work this leads to the minimization of conditional entropy, defined as the expectation (E(·)) of the conditional information I,
H(V|O)=E[I(v|O^)]  (1.32)

[1719] where V represents all the classes and O represents all the observation sequences. Then the mutual information between the classes and observations,
H(V, O)=H(V)−H(V|O)   (1.33)

[1720] become maximized; provided H(V) is constant. This is the reason for calling it Maximum Mutual Information (MMI) criterion. The other name of the method, Maximum A Posteriori (MAP) has the roots in eqn. 1.31 where the a posteriori probability p{v|O^, A} is maximized.

[1721] Even though the eqn.1.31 defines the MMI criterion, it can be rearranged using the Bayes theorem to obtain a better insight, as in eqn.1.34.

[1722] $\begin{array}{cc}\begin{array}{c}{E}_{\mathrm{MMI}}=-\log [\{vO^n,A\}\\ =-\log \frac{p\{v,O^nA\}}{p\{O^nA\}}\\ =-\log \frac{p\{v,O^nA\}}{\sum _{\omega }p\{w,O^nA\}}\end{array}& \left(1.34\right)\end{array}$

[1723] where w represents an arbitrary class.

[1724] If we use an analogous notation as in eqn.1.9, we can write the likelihoods,

[1725] $\begin{array}{cc}{L}_{\mathrm{tot}}^{\mathrm{clamped}}=p\{v,O^n\lambda \}& \left(1.35\right)\\ L_{\mathrm{tot}}^{\mathrm{free}}=\sum _{\omega }p\{w,O^n\lambda \}& \left(1.36\right)\end{array}$

[1726] In the above equations the superscripts clamped and free are used to imply the correct class and all the other classes respectively.

[1727] If we substitute eqns. 1.35 and 1.36 in the eqn.1.34, we get,

[1728] $\begin{array}{cc}{E}_{\mathrm{MMI}}=-\log \frac{L_{\mathrm{tot}}^{\mathrm{clamped}}}{L_{\mathrm{tot}}^{\mathrm{free}}}& \left(1.37\right)\end{array}$

[1729] As in the case of ML re-estimation [ ] or gradient methods can be used to minimize the quantity E_MMI. In the following a gradient based method, which again makes use of the eqn.1.19, is described.

[1730] Since E_MMI is to be minimized, in this case
J=E_MMI,

[1731] and therefore J is directly given by eqn.1.37. The problem then simplifies to the calculation of gradients

[1732] $\frac{\partial J}{\partial \Theta },$
where Θ is an arbitrary parameter of the whole set of HMMs, A. This can be done by differentiating 1.37 with respect to Θ,

[1733] $\begin{array}{cc}\frac{\partial J}{\partial \Theta }=\frac{1}{L_{\mathrm{tot}}^{\mathrm{free}}}\frac{\partial L_{\mathrm{tot}}^{\mathrm{free}}}{\partial \Theta }-\frac{1}{L_{\mathrm{tot}}^{\mathrm{clamped}}}\frac{\partial L_{\mathrm{tot}}^{\mathrm{clamped}}}{\partial \Theta }& \left(1.38\right)\end{array}$

[1734] The same technique, as in the case of ML, can be used to compute the gradients of the likelihoods with respect to the parameters. As a first step likelihoods from eqns.1.35 and 1.36, are expressed in terms of forward and backward variables using the form as in eqn.1.7.

[1735] $\begin{array}{cc}{L}_{\mathrm{tot}}^{\mathrm{clamped}}=\sum _{i\in \mathrm{class}v}{\alpha }_t\left(i\right){\beta }_t\left(i\right)& \left(1.39\right)\\ L_{\mathrm{tot}}^{\mathrm{free}}=\sum _{\omega }\sum _{i\in \mathrm{class}w}{\alpha }_t\left(i\right){\beta }_t\left(i\right)& \left(1.40\right)\end{array}$

[1736] Then the required gradients can be found by differentiating eqns. 1.39 and 1.40. But we consider two cases; one for the transition probabilities and another for the observation probabilities, similar to the case of ML.

[1737] Maximum Mutual Information (MMI) Criterion

[1738] The MMI criterion considers HMMs of all the classes simultaneously, during training. Parameters of the correct model are updated to enhance it's contribution to the observations, while parameters of the alternative models are updated to reduce their contributions. This procedure gives a high discriminative ability to the system and thus MMI belongs to the so called “discriminative training” category.

[1739] In order to have a closer look at the MMI criterion, consider a set of HMMs
A={λ_v, 1≦v≦V}.

[1740] The task is to minimize the conditional uncertainty of a class v of utterances given an observation sequence O^ of that class. This is equivalent minimize the conditional information,
I(v|O^, A)=−log p{v|O^, A}  (1.31)

[1741] with respect to A. In an information theoretical frame work this leads to the minimization of conditional entropy, defined as the expectation (E(·)) of the conditional information I,
H(V|O)=E[I(v|O^)]

[1742] where V represents all the classes and O represents all the observation sequences. Then the mutual information between the classes and observations,
H(V, O)=H(V)−H(V|O)   (1.33)

[1743] become maximized; provided H(V) is constant. This is the reason for calling it Maximum Mutual Information (MMI) criterion. The other name of the method, Maximum A Posteriori (MAP) has the roots in eqn. 1.31 where the a posteriori probability p{v|O^, A} is maximized.

[1744] Even though the eqn.1.31 defines the MMI criterion, it can be rearranged using the Bayes theorem to obtain a better insight, as in eqn.1.34.

[1745] $\begin{array}{cc}\begin{array}{c}{E}_{\mathrm{MMI}}=-\log [\{vO^n,A\}\\ =-\log \frac{p\{v,O^nA\}}{p\{O^nA\}}\\ =-\log \frac{p\{v,O^nA\}}{\sum _{\omega }p\{w,O^nA\}}\end{array}& \left(1.34\right)\end{array}$

[1746] where w represents an arbitrary class.

[1747] If we use an analogous notation as in eqn.1.9, we can write the likelihoods,

[1748] $\begin{array}{cc}{L}_{\mathrm{tot}}^{\mathrm{clamped}}=p\left\{v,O^{″}|\lambda \right\}& \left(1.35\right)\\ L_{\mathrm{tot}}^{\mathrm{free}}=\sum _{w}p\left\{w,O^{″}|\lambda \right\}& \left(1.36\right)\end{array}$

[1749] In the above equations the superscripts clamped and free are used to imply the correct class and all the other classes respectively.

[1750] If we substitute eqns. 1.35 and 1.36 in the eqn.1.34, we get,

[1751] $\begin{array}{cc}{E}_{\mathrm{MMI}}=-\log \frac{L_{\mathrm{tot}}^{\mathrm{clamped}}}{L_{\mathrm{tot}}^{\mathrm{free}}}& \left(1.37\right)\end{array}$

[1752] As in the case of ML re-estimation [ ] or gradient methods can be used to minimize the quantity E_MMI. In the following a gradient based method, which again makes use of the eqn.1.19, is described.

[1753] Since E_MMI is to be minimized, in this case
J=E_MMI,

[1754] and therefore J is directly given by eqn.1.37. The problem then simplifies to the calculation of gradients

[1755] $\frac{\partial J}{\partial \Theta },$
where Θ is an arbitrary parameter of the whole set of HMMs, A. This can be done by differentiating 1.37 with respect to Θ,

[1756] $\begin{array}{cc}\frac{\partial J}{\partial \Theta }=\frac{1}{L_{\mathrm{tot}}^{\mathrm{free}}}\frac{\partial L_{\mathrm{tot}}^{\mathrm{free}}}{\partial \Theta }-\frac{1}{L_{\mathrm{tot}}^{\mathrm{clamped}}}\frac{\partial L_{\mathrm{tot}}^{\mathrm{clamped}}}{\partial \Theta }& \left(1.38\right)\end{array}$

[1757] The same technique, as in the case of ML, can be used to compute the gradients of the likelihoods with respect to the parameters. As a first step likelihoods from eqns.1.35 and 1.36, are expressed in terms of forward and backward variables using the form as in eqn.1.7.

[1758] $\begin{array}{cc}{L}_{\mathrm{tot}}^{\mathrm{clamped}}=\sum _{i\in \mathrm{class}v}{\alpha }_t\left(i\right){\beta }_t\left(i\right)& \left(1.39\right)\\ L_{\mathrm{tot}}^{\mathrm{free}}=\sum _{\omega }\sum _{i\in \mathrm{class}w}{\alpha }_t\left(i\right){\beta }_k\left(i\right)& \left(1.40\right)\end{array}$

[1759] Then the required gradients can be found by differentiating eqns. 1.39 and 1.40. But we consider two cases; one for the transition probabilities and another for the observation probabilities, similar to the case of ML.

[1760] Gradient With Respect to Transition Probabilities

[1761] Using the chain rule for any of the likelihoods, free or clamped,

[1762] $\begin{array}{cc}\frac{\partial L_{\mathrm{tot}}^{(-)}}{\partial a_{\mathrm{ij}}}=\sum _{t=1}^T\frac{\partial L_{\mathrm{tot}}^{(-)}}{\partial {\alpha }_t\left(j\right)}\frac{\partial {\alpha }_t\left(j\right)}{\partial a_{\mathrm{ij}}}& \left(1.41\right)\end{array}$

[1763] Differentiating eqns.1.39 and 1.40 with respect to α_t(j), to get two results for free and clamped cases and using the common result in eqn.1.25, we get substitutions for both terms on the right hand side of eqn. 1.41. This substitution yields two separate results for free and clamped cases.

[1764] $\begin{array}{cc}\frac{\partial L_{\mathrm{tot}}^{\mathrm{clamped}}}{\partial a_{\mathrm{ij}}}={\delta }_{\mathrm{kv}}\sum _{\underset{i\in \mathrm{class}k}{t=1}}^T{\beta }_t\left(j\right)b_j\left(a_t\right){\alpha }_{t-1}\left(i\right),& \left(1.42\right)\end{array}$

[1765] where δ_kv is a Kronecker delta.

[1766] $\begin{array}{cc}\frac{\partial L_{\mathrm{tot}}^{\mathrm{free}}}{\partial a_{\mathrm{ij}}}=\sum _{t=1}^T{\beta }_t\left(j\right)b_j\left(a_t\right){\alpha }_{t-1}\left(i\right)& \left(1.43\right)\end{array}$