
Neural Network Models
Theory and Projects
Philippe De Wilde(Author)
Springer (Publisher)
2nd Edition
Published on 30. May 1997
Book
Paperback/Softback
XI, 174 pages
978-3-540-76129-7 (ISBN)
Description
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.
More details
Edition
Second Edition 1997
Language
English
Place of publication
London
United Kingdom
Publishing group
Springer Berlin
Target group
Primary & secondary/elementary & high school
Graduate
Illustrations
XI, 174 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
295 gr
ISBN-13
978-3-540-76129-7 (9783540761297)
DOI
10.1007/978-1-84628-614-8
Schweitzer Classification
Other editions
Previous edition
Book
12/1995
Springer
€85.59
Article exhausted; check for reprint
Content
1 Key concepts in neural networks.- 2 Backpropagation.- 3 Neurons in the Brain.- 4 The Fundamental System of Differential Equations.- 5 Synchronous and Discrete Networks.- 6 Linear Capacity.- 7 Capacity from a Signal to Noise Ratio.- 8 Neural Networks and Markov Chains.