Titlebook: Distributed Decision Making and Control; Rolf Johansson,Anders Rantzer Book 2012 Springer London 2012 Autonomous Systems.Control Theory.De

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書目名稱Distributed Decision Making and Control網(wǎng)絡(luò)公開度




書目名稱Distributed Decision Making and Control網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Distributed Decision Making and Control被引頻次學(xué)科排名




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尾隨

Decentralized Control with Communication Bandwidth Constraintsecentralized stabilization problem of a linear time-invariant (LTI) plant by multiple control stations that receive sensing information through rate-limited channels, and these stations are not capable of communicating with each other directly. The main result of the this chapter is a sufficient con

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Monotone Games for Cognitive Radio Systemsg selfishly to optimize his own well-being. In this chapter, we present a mathematical treatment of (generalized) Nash equilibrium problems based on the variational inequality and complementarity approach, covering the topics of existence and uniqueness of an equilibrium, and the design of distribut

Alcove

Generic-Drug

Recursive Bargaining with Dynamic Accumulationrd problem of how to divide a surplus for their own consumption, parties face the additional problem of how much to invest, knowing that the level of investment affects the surplus available in the next period. We provide an algorithm to solve the game when the number of bargaining stages is finite

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itinerary

Performance Prediction in Uncertain Multi-Agent Systems Using , Adaptation-Based Distributed Event-Ts with embedded . adaptive controllers. A communication and adaptation co-design scheme is proposed that helps to predict system performance. With this scheme, an agent locally determines its broadcast time instants using distributed event-triggering. The embedded . adaptive controller enables each

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Dynamic Coverage and Clustering: A Maximum Entropy Approachose that arise in the deployment of mobile sensor networks to the identification of ensemble spike trains in computational neuroscience applications. This framework provides for the identification of natural clusters in an underlying dataset, while addressing inherent tradeoffs such as those between