• Produktbild: Stochastic Approximation and Recursive Algorithms and Applications
  • Produktbild: Stochastic Approximation and Recursive Algorithms and Applications
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Stochastic Approximation and Recursive Algorithms and Applications

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

17.07.2003

Abbildungen

XXII, 478 p.

Verlag

Springer Us

Seitenzahl

478

Maße (L/B/H)

24,1/16,2/3 cm

Gewicht

834 g

Auflage

Second Edition 2003

Sprache

Englisch

ISBN

978-0-387-00894-3

Beschreibung

Rezension

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)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

17.07.2003

Abbildungen

XXII, 478 p.

Verlag

Springer Us

Seitenzahl

478

Maße (L/B/H)

24,1/16,2/3 cm

Gewicht

834 g

Auflage

Second Edition 2003

Sprache

Englisch

ISBN

978-0-387-00894-3

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Stochastic Approximation and Recursive Algorithms and Applications
  • Produktbild: Stochastic Approximation and Recursive Algorithms and Applications
  • Introduction: Applications and Issues.- Applications to Learning, Repeated Games, State Dependent Noise, and Queue Optimization.- Applications in Signal Processing, Communications, and Adaptive Control.- Mathematical Background.- Convergence with Probability One: Martingale Difference Noise.- Convergence with Probability One: Correlated Noise.- Weak Convergence: Introduction.- Weak Convergence Methods for General Algorithms.- Applications: Proofs of Convergence.- Rate of Convergence.- Averaging of the Iterates.- Distributed/Decentralized and Asynchronous Algorithms.