Learning Automata and Stochastic Optimization
Author:   A.S. Poznyak ,  K. Najim
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   1997 ed.
Volume:   225
ISBN:  

9783540761549


Pages:   207
Publication Date:   12 March 1997
Format:   Paperback
Availability:   Out of stock   Availability explained
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Learning Automata and Stochastic Optimization


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Overview

In the last decade there has been a steadily growing need for and interest in computational methods for solving stochastic optimization problems with or wihout constraints. Optimization techniques have been gaining greater acceptance in many industrial applications, and learning systems have made a significant impact on engineering problems in many areas, including modelling, control, optimization, pattern recognition, signal processing and diagnosis. Learning automata have an advantage over other methods in being applicable across a wide range of functions. Featuring new and efficient learning techniques for stochastic optimization, and with examples illustrating the practical application of these techniques, this volume will be of benefit to practicing control engineers and to graduate students taking courses in optimization, control theory or statistics.

Full Product Details

Author:   A.S. Poznyak ,  K. Najim
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   1997 ed.
Volume:   225
Dimensions:   Width: 15.50cm , Height: 1.20cm , Length: 23.50cm
Weight:   0.350kg
ISBN:  

9783540761549


ISBN 10:   3540761543
Pages:   207
Publication Date:   12 March 1997
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Stochastic optimization.- On learning automata.- Unconstrained optimization problems.- Constrained optimization problems.- Optimization of nonstationary functions.

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