Authors:
- Unique selling points: - The book has been carefully written so that no prior knowledge of neural networks and genetic algorithms is needed - The author illustrates the basic principles of evolutionary learning algorithms by applying them to adaptive control problems - The book includes a chapter devoted to artificial neural networks, which is one of the most active areas of research at the moment
Part of the book series: Perspectives in Neural Computing (PERSPECT.NEURAL)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Department of Computer Science, Brunel University, Uxbridge, Middlesex, UK
Dimitris C. Dracopoulos
Bibliographic Information
Book Title: Evolutionary Learning Algorithms for Neural Adaptive Control
Authors: Dimitris C. Dracopoulos
Series Title: Perspectives in Neural Computing
DOI: https://doi.org/10.1007/978-1-4471-0903-7
Publisher: Springer London
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London Limited 1997
Softcover ISBN: 978-3-540-76161-7Published: 15 August 1997
eBook ISBN: 978-1-4471-0903-7Published: 21 December 2013
Series ISSN: 1431-6854
Edition Number: 1
Number of Pages: XI, 211
Number of Illustrations: 14 b/w illustrations
Topics: Artificial Intelligence, Complexity