Cover image for Neural computing : theory and practice
Neural computing : theory and practice
Wasserman, Philip D., 1937-
Personal Author:
Publication Information:
New York : Van Nostrand Reinhold, [1989]

Physical Description:
viii, 230 pages : illustrations ; 24 cm
Subject Term:
Format :


Call Number
Material Type
Home Location
Central Library QA76.5 .W353 1989 Adult Non-Fiction Central Closed Stacks

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Explains clearly the major algorithms and demystifies the rigorous mathematics involved in neural networks. Starts with English language explanations of particular topics and builds toward general principles. Annotation copyrighted by Book News, Inc., Portland, OR

Reviews 1

Choice Review

Neural network research in computer science and engineering applications is an important and emerging field. Wasserman provides the basic introduction to the theory and practice of computing with artificial neural networks. There are many books published in this area that deal with the neuro-scientific aspects of true neural networks but not many that deal with the engineering aspects of artificial neural networks. This book by a noted author is written for nontechnical professionals who wish to learn the basic principles of neural networks. The contents cover simple networks such as the perceptrons, counterpropagation networks, Hopfield nets, and bidirectional associative memories, and basic network strategies such as backpropagation and adaptive resonance theory. The writing style is descriptive, interpretive, and nontechnical, and the presentation is well illustrated. References are provided at the end of each chapter for further reading. Highly recommended for libraries serving upper-division undergraduates and above in engineering and information sciences. -J. Y. Cheung, University of Oklahoma

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