Neural Network Models: Theory and Projects

Wilde, Philippe de

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.

Details

Published by: Springer

Publication Date: 1997-05-30

Format: Paperback

ISBN-13: 9783540761297

DOI: 10.1007/978-1-84628-614-8

Dimensions: 235cm x155cm

Pages: 174