
Neural Networks
P.D. Picton(Author)
Red Globe Press
Published on 5. October 2000
Book
Paperback/Softback
XII, 195 pages
978-0-333-80287-8 (ISBN)
Description
Neural Networks provides a gentle introduction to the subject, for undergraduates from Computer Science and Electrical Engineering degrees.
This updated and revised second edition assumes no prior knowledge and sets out to describe what neural nets are, what they do, and how they do it. The main networks covered include ADALINE, WISARD, the Hopfield Network, Bidirectional Associative Memory, the Boltzmann machine, counter-propogation and ART networks, and Kohonen's self-organizing maps. These networks are discussed by means of examples, giving the reader a good overall knowledge of current developments in the field.
This updated and revised second edition assumes no prior knowledge and sets out to describe what neural nets are, what they do, and how they do it. The main networks covered include ADALINE, WISARD, the Hopfield Network, Bidirectional Associative Memory, the Boltzmann machine, counter-propogation and ART networks, and Kohonen's self-organizing maps. These networks are discussed by means of examples, giving the reader a good overall knowledge of current developments in the field.
More details
Series
Edition
2nd ed. 2000
Language
English
Place of publication
London
United Kingdom
Publishing group
Bloomsbury Publishing PLC
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 254 mm
Width: 203 mm
Thickness: 11 mm
Weight
458 gr
ISBN-13
978-0-333-80287-8 (9780333802878)
DOI
10.1057/9780333985731
Schweitzer Classification
Other editions
Additional editions
Book
Palgrave Macmillan
€151.79
The article will not be published
Previous edition

Phil Picton
Neural Networks
Book
05/1994
Palgrave Macmillan
€22.27
Article exhausted; check for reprint
Person
PHIL PICTON is a Reader in Engineering Control Systems at Nene College in Northampton. Prior to this he was a lecturer at the Open University where he contributed to distance learning courses on control engineering, electronics, mechatronics and artificial intelligence. His research interests include patten recognition, intelligent control and logic design.
Content
Preface.- Introduction.- ADALINE.- Perceptrons.- Boolean Neural Networks.- Associative Memory and Feedback Networks.- Statistical Neural Networks.- Self-organizing Networks.- Neural Networks in Control Engineering.- Threshold Logic.- Implementation.- Conclusions.- Appendix A Derivation of the Delta Rule.- References.