Stochastic Approximation Methods for Constrained and Unconstrained Systems
The book deals with a powerful and convenient approach to a great variety of types of problems of the recursive monte-carlo or stochastic approximation type. Such recu- sive algorithms occur frequently in stochastic and adaptive control and optimization t
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Lawrence Sirovich
Courant Institute of Mathematical Sciences New York University New York, N.Y. 10012
Division of Applied Mathematics Brown University Providence, R.I. 02912
Joseph P. LaSalle
Gerald B. Whitham
Division of Applied Mathematics Brown University Providence, R.L 02912
Applied Mathematics Firestone Laboratory California Institute of Technology Pasadena, CA.91125
EDITORIAL STATEMENT The mathematization of all sciences, the fading of traditional scientific boundaries, the impact of computer technology, the growing importance of mathematicalcomputer modelling and the necessity of scientific planning all create the need both in education and research for books that are introductory to and abreast of these developments. The purpose of this series is to provide such books, suitable for the user of mathematics, the mathematician interested in applications, and the student scientist. In particular, this series will provide an outlet for material less formally presented and more anticipatory of needs than finished texts or monographs, yet of immediate interest because of the novelty of its treatment of an application or of mathematics being applied or Iying close to applications. The aim of the series is, through rapid publication in an attractive but inexpensive format, to make material of current interest widely accessible. This implies the absence of excessive generality and abstraction, and unrealistic idealization, but with quality of exposition as a goal. Many of the books will originate out of and will stimulate the development of new undergraduate and graduate courses in the applications of mathematics. Some of the books will present introductions to new areas of research, new applications and act as signposts for new directions in the mathematical sciences. This series will often serve as an intermediate stage of the publication of material which, through exposure here, will be further developed and refined. These will appear in conventional format and in hard cover.
MANUSCRIPTS The Editors welcome all inquiries regarding the submission of manuscripts for the series. Final preparation of all manuscripts will take place in the editorial offices of the series in the Division of Applied Mathematics, Brown University, Providence, Rhode Island. SPRINGER-VERLAG NEW YORK INe., 175 Fifth Avenue, New York, N. Y. 10010
Applied Mathematical Sciences I Volume 26
Harold J. Kush ner Dean S. Clark
Stochastic Approximation Methods for Constrained and Unconstrained Systems
Springer-Verlag
New York
Heidelberg
Berlin
Harold J. Kushner Division of Applied Mathematics Brown University Providence, Rhode Island USA
Dean S. Clark Division of Applied Mathematics Brown University Providence, Rhode Island USA
AMS Classifications: 41A65, 34F05, 60H10, 60H15, 62N15, 93E10
Ubrary of Congress Cataloging in Publication Data
Kushner, Harold Joseph, 1933Stochastic approximation methods for constrained and unconstrained systems. (Applied mathematical sciences; 26) Bibliography: p. Includes index. 1. Stochastic appro
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