Neural Networks: An Introduction

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Springer Science & Business Media, 02.10.1995 - 331 Seiten
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.
 

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Seite 320 - Stock Performance Modeling Using Neural Networks: A Comparative Study with Regression Models", Neural Network, V'ol 5, 1994, pp961-970.
Seite 321 - The Synaptic Organization of the Brain (Oxford University Press, New York, 1979.) 22.
Seite 320 - LE Reichl, A Modern Course in Statistical Mechanics, University of Texas Press, Austin, TX 91980, 1980, p.
Seite 320 - A. (1988). Perception of left and right by a feed forward net.
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