Stochastic Approximation and Its Applications / Edition 1

Stochastic Approximation and Its Applications / Edition 1

by Han-Fu Chen
Pub. Date:
Springer US


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Stochastic Approximation and Its Applications / Edition 1

This book presents the recent development of shastic approximation algorithms with expanding truncations based on the TS (trajectory-subsequence) method, a newly developed method for convergence analysis. This approach is so powerful that conditions used for guaranteeing convergence have been considerably weakened in comparison with those applied in the classical probability and ODE methods. The general convergence theorem is presented for sample paths and is proved in a purely deterministic way. The sample-path description of theorems is particularly convenient for applications. Convergence theory takes both observation noise and structural error of the regression function into consideration. Convergence rates, asymptotic normality and other asymptotic properties are presented as well. Applications of the developed theory to global optimization, blind channel identification, adaptive filtering, system parameter identification, adaptive stabilization and other problems arising from engineering fields are demonstrated.

Product Details

ISBN-13: 9781402008061
Publisher: Springer US
Publication date: 08/31/2002
Series: Nonconvex Optimization and Its Applications , #64
Edition description: 2002
Pages: 360
Product dimensions: 6.14(w) x 9.21(h) x 0.04(d)

Table of Contents

Preface. Acknowledgments. 1. Robbins-Monro Algorithm. 2. Shastic Approximation Algorithms with Expanding Truncations. 3. Asymptotic Properties of Shastic Approximation Algorithms. 4. Optimization by Shastic Approximation. 5. Applications To Signal Processing. 6. Application to Systems and Control. 7. Appendices. References. Index.

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