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Stochastic approximation algorithms and applications /

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The book presents a comprehensive development of the modern theory of stochastic approximation, or recursive stochastic algorithms, for both constrained and unconstrained problems, with step sizes that either go to zero or are constant and small (and perhaps random). The general motivation arises fr...

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Bibliographic Details
Main Author: Kushner, Harold J. (Harold Joseph), 1933-
Corporate Author: SpringerLink (Online service)
Other Authors: Yin, George, 1954-
Format: eBook
Language:English
Published: New York : Springer, [1997]
Series:Applications of mathematics ; 35.
Subjects:
Stochastic approximation.
contrainte.
algorithme distribué.
algorithme asynchrone.
convergence faible.
convergence.
équation différentielle ordinaire.
algorithme stochastique.
approximation stochastique.
Stochastische methoden.
Benaderingen (wiskunde)
Ruis.
Martingalen.
Approximation stochastique.
Stochastische Approximation.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 1. Introduction: Applications and Issues
  • 2. Applications to Learning, State Dependent Noise, and Queueing
  • 3. Applications in Signal Processing and Adaptive Control
  • 4. Mathematical Background
  • 5. Convergence with Probability One: Martingale Difference Noise
  • 6. Convergence with Probability One: Correlated Noise
  • 7. Weak Convergence: Introduction
  • 8. Weak Convergence Methods for General Algorithms
  • 9. Applications: Proofs of Convergence
  • 10. Rate of Convergence
  • 11. Averaging of the Iterates
  • 12. Distributed/Decentralized and Asynchronous Algorithms.