Stochastic approximation and optimization of random systems
General Material Designation
[Book]
First Statement of Responsibility
Lennart Ljung, Georg Pflug, Harro Walk.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Basel ; Boston
Name of Publisher, Distributor, etc.
Birkhäuser Verlag
Date of Publication, Distribution, etc.
1992
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
(113 pages) : illustrations
SERIES
Series Title
DMV Seminar, Bd. 17.
GENERAL NOTES
Text of Note
The DMV seminar 'Stochastische Approximation und Optimierung zufällger Systeme' was held at Blaubeuren, 28.5-4.6.1989--Preface.
CONTENTS NOTE
Text of Note
I Foundations of stochastic approximation --; §1 Almost sure convergence of stochastic approximation procedures --; §2 Recursive methods for linear problems --; §3 Stochastic optimization under stochastic constraints --; §4 A learning model; recursive density estimation --; §5 Invariance principles in stochastic approximation --; §6 On the theory of large deviations --; References for Part I --; II Applicational aspects of stochastic approximation --; §7 Markovian stochastic optimization and stochastic approximation procedures --; §8 Asymptotic distributions --; §9 Stopping times --; §10 Applications of stochastic approximation methods --; References for Part II --; III Applications to adaptation algorithms --; §11 Adaptation and tracking --; §12 Algorithm development --; §13 Asymptotic Properties in the decreasing gain case --; §14 Estimation of the tracking ability of the algorithms --; References for Part III.
SUMMARY OR ABSTRACT
Text of Note
The DMV seminar "Stochastische Approximation und Optimierung zufalliger Systeme" was held at Blaubeuren, 28. 5.-4. 6. 1989. The goal was to give an approach to theory and application of stochasƯ tic approximation in view of optimization problems, especially in engineering systems. These notes are based on the seminar lectures. They consist of three parts: I. Foundations of stochastic approximation (H. Walk); n. Applicational aspects of stochastic approximation (G. PHug); In. Applications to adaptation :ugorithms (L. Ljung). The prerequisites for reading this book are basic knowledge in probability, mathematical statistics, optimization. We would like to thank Prof. M. Barner and Prof. G. Fischer for the orƯ ganization of the seminar. We also thank the participants for their cooperation and our assistants and secretaries for typing the manuscript. November 1991 L. Ljung, G. PHug, H. Walk Table of contents I Foundations of stochastic approximation (H. Walk) ʹ1 Almost sure convergence of stochastic approximation procedures 2 ʹ2 Recursive methods for linear problems 17 ʹ3 Stochastic optimization under stochastic constraints 22 ʹ4 A learning model; recursive density estimation 27 ʹ5 Invariance principles in stochastic approximation 30 ʹ6 On the theory of large deviations 43 References for Part I 45 11 Applicational aspects of stochastic approximation (G. PHug) ʹ7 Markovian stochastic optimization and stochastic approximation procedures 53 ʹ8 Asymptotic distributions 71 ʹ9 Stopping times 79 ʹ1O Applications of stochastic approximation methods 80 References for Part II 90 III Applications to adaptation algorithms (L.