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Table of contents (8 chapters)
Keywords
About this book
Providing an in-depth treatment of neural network models, this volume explains and proves the main results in a clear and accessible way. It presents the essential principles of nonlinear dynamics as derived from neurobiology, and investigates the stability, convergence behaviour and capacity of networks. Also included are sections on stochastic networks and simulated annealing, presented using Markov processes rather than statistical physics, and a chapter on backpropagation. Each chapter ends with a suggested project designed to help the reader develop an integrated knowledge of the theory, placing it within a practical application domain. Neural Network Models: Theory and Projects concentrates on the essential parameters and results that will enable the reader to design hardware or software implementations of neural networks and to assess critically existing commercial products.
Authors and Affiliations
Bibliographic Information
Book Title: Neural Network Models
Book Subtitle: Theory and Projects
Authors: Philippe Wilde
DOI: https://doi.org/10.1007/978-1-84628-614-8
Publisher: Springer London
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 1997
Softcover ISBN: 978-3-540-76129-7Published: 30 May 1997
eBook ISBN: 978-1-84628-614-8Published: 29 June 2013
Edition Number: 2
Number of Pages: XI, 174
Additional Information: Originally published as Volume 210 in the series: Lecture Notes Control