Stochastic Approximation and Recursive Algorithms and Applications
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ISBN-13:
9780387008943
Veröffentl:
2003
Erscheinungsdatum:
17.07.2003
Seiten:
478
Autor:
Harold Kushner
Gewicht:
834 g
Format:
241x162x30 mm
Sprache:
Englisch
Beschreibung:
This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as well as more detailed discussion.
The book presents a thorough development of the modern theory ofstochastic approximation or recursive stochastic algorithms for bothconstrained and unconstrained problems. The assumptions and proofmethods are designed to cover the needs of recent applications. Thedevelopment proceeds from simple to complex problems, allowing theunderlying ideas to be more easily understood. Many examplesillustrate the application of the theory.This second edition is a thorough revision, although the main featuresand the structure remain unchanged. It contains many additionalapplications and results, and more detailed discussion.
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.
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