Overview
- Authors:
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Berndt Müller
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Department of Physics, Duke University, Durham, USA
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Joachim Reinhardt
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Institut für Theoretische Physik, J.-W.-Goethe-Universität, Frankfurt, Germany
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Michael T. Strickland
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Department of Physics, Duke University, Durham, USA
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Table of contents (29 chapters)
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Models of Neural Networks
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 3-12
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 13-23
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 24-37
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 38-45
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 46-51
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 52-62
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 63-71
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 72-92
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 93-107
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 108-125
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 126-134
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 135-143
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 144-150
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 151-161
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 162-173
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 174-187
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Statistical Physics of Neural Networks
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Front Matter
Pages 189-189
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- Berndt Müller, Joachim Reinhardt, Michael T. Strickland
Pages 191-200
About this book
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.
Reviews
"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