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Stochastic Approximation Algorithms and Applications
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| 概要 | In recent years algorithms of the stochastic approximation type have found applications in new and diverse areas, and new techniques have been developed for proofs of convergence and rate of convergen...ce. The actual and potential applications in signal processing have exploded. New challenges have arisen in applications to adaptive control. This book presents a thorough coverage of the ODE method used to analyze these algorithms.続きを見る |
| 目次 | 1 Introduction: Applications and Issues 2 Applications to Learning, State Dependent Noise, and Queueing 3 Applications in Signal Processing and Adaptive Control 4 Mathematical Background 5 Convergence with Probability One: Martingale Difference Noise 6 Convergence with Probability One: Correlated Noise 7 Weak Convergence: Introduction 8 Weak Convergence Methods for General Algorithms 9 Applications: Proofs of Convergence 10 Rate of Convergence 11 Averaging of the Iterates 12 Distributed/Decentralized and Asynchronous Algorithms References Symbol Index.続きを見る |
| 本文を見る | Full text available from SpringerLink ebooks - Mathematics and Statistics (Archive) |
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| 登録日 | 2020.06.27 |
| 更新日 | 2020.06.28 |