Learning automata and stochastic optimization /
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...
| Main Author: | |
|---|---|
| Corporate Author: | |
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer,
[1997]
|
| Series: | Lecture notes in control and information sciences ;
225. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | 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. |
|---|---|
| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource. |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9783540409380 (electronic bk.) 3540409386 (electronic bk.) |