Stochastic Approximation and Recursive Algorithms and Applications
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Beschreibung
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 convergence. 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.
This book on stochastic approximation by one of the leading researchers in the field summarizes recent results. In addition to developing the theory, it includes two full chapters on applications to learning models, neural nets, and signal processing and control.
Autor*in
Harold Kushner
Themen in »Stochastic Approximation and Recursive Algorithms and Applications«
Markov chain Martingal Martingale Variance diffusion process jump diffusion probability random walk stochastic differential equation
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From the reviews of the second edition:
"This is the second edition of an excellent book on stochastic approximation, recursive algorithms and applications … . Although the structure of the book has not been changed, the authors have thoroughly revised it and added additional material … ." (Evelyn Buckwar, Zentralblatt MATH, Vol. 1026, 2004)
"The book attempts to convince that … algorithms naturally arise in many application areas … . I do not hesitate to conclude that this book is exceptionally well written. The literature citation is extensive, and pertinent to the topics at hand, throughout. This book could be well suited to those at the level of the graduate researcher and upwards." (A. C. Brooms, Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 169 (3), 2006)
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