Berndt Müller Joachim Reinhardt Michael T. Strickland Müller Neural Networks

Neural Networks

von Berndt Müller Joachim Reinhardt Michael T. Strickland

An Introduction

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Beschreibung

Neural Networks The concepts of neural-network models and techniques of parallel distributed processing are comprehensively presented in a three-step approach: - After a brief overview of the neural structure of the brain and the history of neural-network modeling, the reader is introduced to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers more advanced subjects such as the statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - In the self-contained final part, seven programs that provide practical demonstrations of neural-network models and their learning strategies are discussed. The software is included on a 3 1/2-inch MS-DOS diskette. The source code can be modified using Borland's TURBO-C 2.0 compiler, the Microsoft C compiler (5.0), or compatible compilers.
Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.

Autor*in

Berndt Müller

Themen in »Neural Networks«

Nervous System algorithms evolutionary algorithm genetic algorithms learning neurons optimization statistical physics

Stimmen zu »Neural Networks«

"I have enjoyed using the previous edition of this well-known book both as a personal text and as a class manual. Although it claims to be only an introduction, it contains a wealth of material and addresses real problems in physics." Computing Reviews
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Details

ISBN: 9783642577604
Verlag: Springer Berlin
Erscheinung: 06.12.2012

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