Neural networks

a comprehensive foundation

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Last edited by Drini
September 13, 2025 | History

Neural networks

a comprehensive foundation

  • 8 Want to read

This book represents the most comprehensive treatment available of neural networks from an engineering perspective. Thorough, well-organized, and completely up to date, it examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.

Written in a concise and fluid manner, by a foremost engineering textbook author, to make the material more accessible, this book is ideal for professional engineers and graduate students entering this exciting field. Computer experiments, problems, worked examples, a bibliography, photographs, and illustrations reinforce key concepts.

Publish Date
Language
English
Pages
696

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Previews available in: English

Edition Availability
Cover of: Neural networks
Neural networks: a comprehensive foundation
1999, Prentice Hall
in English - 2nd ed.
Cover of: Neural networks
Neural networks: a comprehensive foundation
1994, Macmillan, Maxwell Macmillan Canada, Maxwell Macmillan International
in English

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Book Details


Edition Notes

Includes bibliographical references (p. 635-690) and index.

Published in
New York, Toronto, New York

Classifications

Dewey Decimal Class
006.3
Library of Congress
QA76.87 .H39 1994, QA76.87.H39 1994

The Physical Object

Pagination
xix, 696 p. :
Number of pages
696

Edition Identifiers

Open Library
OL1418264M
Internet Archive
neuralnetworksco00hayk
ISBN 10
0023527617
LCCN
93028092
OCLC/WorldCat
28377313
LibraryThing
294250
Goodreads
4127520

Work Identifiers

Work ID
OL1824445W

Work Description

This book represents the most comprehensive treatment available of neural networks from an engineering perspective. Thorough, well-organized, and completely up to date, it examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.

Written in a concise and fluid manner, by a foremost engineering textbook author, to make the material more accessible, this book is ideal for professional engineers and graduate students entering this exciting field. Computer experiments, problems, worked examples, a bibliography, photographs, and illustrations reinforce key concepts.

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September 13, 2025 Edited by Drini Edited without comment.
July 17, 2024 Edited by MARC Bot import existing book
July 13, 2024 Edited by MARC Bot import existing book
December 19, 2023 Edited by ImportBot import existing book
December 9, 2009 Created by WorkBot add works page