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Stochastic Approximation and Recursive Algorithms and Applications

  • Book
  • © 1997

Overview

Authors:
  1. Harold J. Kushner

    1. Division of Applied Mathematics, Brown University, Providence, USA

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    You can also search for this author in PubMed   Google Scholar

  2. G. George Yin

    1. Department of Mathematics, Wayne State University, Detroit, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Stochastic Modelling and Applied Probability (SMAP, volume 35)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xxi
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  2. Introduction: Applications and Issues

    • Harold J. Kushner, G. George Yin
    Pages 1-24

  3. Applications to Learning, State Dependent Noise, and Queueing

    • Harold J. Kushner, G. George Yin
    Pages 25-46

  4. Applications in Signal Processing and Adaptive Control

    • Harold J. Kushner, G. George Yin
    Pages 47-66

  5. Mathematical Background

    • Harold J. Kushner, G. George Yin
    Pages 67-83

  6. Convergence with Probability One: Martingale Difference Noise

    • Harold J. Kushner, G. George Yin
    Pages 85-133

  7. Convergence with Probability One: Correlated Noise

    • Harold J. Kushner, G. George Yin
    Pages 135-184

  8. Weak Convergence: Introduction

    • Harold J. Kushner, G. George Yin
    Pages 185-212

  9. Weak Convergence Methods for General Algorithms

    • Harold J. Kushner, G. George Yin
    Pages 213-250

  10. Applications: Proofs of Convergence

    • Harold J. Kushner, G. George Yin
    Pages 251-272

  11. Rate of Convergence

    • Harold J. Kushner, G. George Yin
    Pages 273-325

  12. Averaging of the Iterates

    • Harold J. Kushner, G. George Yin
    Pages 327-346

  13. Distributed/Decentralized and Asynchronous Algorithms

    • Harold J. Kushner, G. George Yin
    Pages 347-391

  14. Back Matter

    Pages 393-417
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Keywords

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)

Authors and Affiliations

  • Division of Applied Mathematics, Brown University, Providence, USA

    Harold J. Kushner

  • Department of Mathematics, Wayne State University, Detroit, USA

    G. George Yin

Bibliographic Information

  • Book Title: Stochastic Approximation and Recursive Algorithms and Applications

  • Authors: Harold J. Kushner, G. George Yin

  • Series Title: Stochastic Modelling and Applied Probability

  • DOI: https://doi.org/10.1007/978-1-4899-2696-8

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag New York 1997

  • eBook ISBN: 978-1-4899-2696-8Published: 11 November 2013

  • Series ISSN: 0172-4568

  • Series E-ISSN: 2197-439X

  • Edition Number: 1

  • Number of Pages: XXI, 417

  • Topics: Probability Theory and Stochastic Processes

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