Evolutionary Learning Algorithms for Neural Adaptive Control by Dimitris C. Dracopoulos.

Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfac...

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Bibliographic Details
Main Author: Dracopoulos, Dimitris C. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: London : Springer London : Imprint: Springer, 1997.
Edition:1st ed. 1997.
Series:Perspectives in Neural Computing,
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary:Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.
Physical Description:XI, 211 p. 14 illus. online resource.
ISBN:9781447109037
ISSN:1431-6854
DOI:10.1007/978-1-4471-0903-7