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Neural Networks (Grassroots Series)

Phil Picton

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ISBN 10: 0333948998 / ISBN 13: 9780333948996
Published by Palgrave Macmillan, 2000
New Condition: Brand New Hardcover
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2nd edition. 195 pages. 9.75x7.50x0.50 inches. In Stock. Bookseller Inventory # 0333948998

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Bibliographic Details

Title: Neural Networks (Grassroots Series)

Publisher: Palgrave Macmillan

Publication Date: 2000

Binding: Hardcover

Book Condition:Brand New

About this title


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, 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.

From the Back Cover:

Neural Networks, Second Edition provides a complete introduction to neural networks. It describes what they are, what they can do, and how they do it. While some scientific background is assumed, the reader is not expected to have any prior knowledge of neural networks. These networks are explained and discussed by means of examples, so that by the end of the book the reader will have a good overall knowledge of developments right up to current work in the field.

· Updated and expanded second edition
· Main networks covered are: feedforward networks such as the multilayered perceptron, Boolean networks such as the WISARD, feedback networks such as the Hopfield network, statistical networks such as the Boltzmann machine and Radial-Basis function networks, and self-organising networks such as Kohonen's self-organizing maps. Other networks are referred to throughout the text to give historical interest and alternative architectures
· The applications discussed will appeal to student engineers and computer scientists interested in character recognition, intelligent control and threshold logic. The final chapter looks at ways of implementing a neural network, including electronic and optical systems

This book is suitable for undergraduates from Computer Science and Electrical Engineering Courses who are taking a one module course on neural networks, and for researchers and computer science professionals who need a quick introduction to the subject.

PHIL PICTON is Professor of Intelligent Computer Systems at University College 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 pattern recognition, intelligent control and logic design.

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