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Stochastic Modelling and Applied Probability

Stochastic Approximation and Recursive Algorithms and Applications

Authors: Kushner, Harold, Yin, George

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About this book

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.

Reviews

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)


Table of contents (12 chapters)

Table of contents (12 chapters)

Buy this book

eBook $74.99
price for USA in USD
  • ISBN 978-1-4899-2696-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
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Bibliographic Information

Bibliographic Information
Book Title
Stochastic Approximation and Recursive Algorithms and Applications
Authors
Series Title
Stochastic Modelling and Applied Probability
Series Volume
35
Copyright
1997
Publisher
Springer-Verlag New York
Copyright Holder
Springer-Verlag New York
eBook ISBN
978-1-4899-2696-8
DOI
10.1007/978-1-4899-2696-8
Series ISSN
0172-4568
Edition Number
1
Number of Pages
XXI, 417
Topics