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 "neural" information processing, i.e. associative memory, perceptrons, feature-sensitive networks, learning strategies, and practical applications. - Part 2 covers more advanced subjects such as spin glasses, the mean-field theory of the Hopfield ...
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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 "neural" information processing, i.e. associative memory, perceptrons, feature-sensitive networks, learning strategies, and practical applications. - Part 2 covers more advanced subjects such as spin glasses, the mean-field theory of the Hopfield model, and the space of interactions in neural networks. - The self-contained final part discusses seven programs that provide practical demonstrations of neural-network models and their learning strategies. Ample opportunity is given to improve and modify the source codes. The software is included on a 5 1/4 inch MS DOS diskette and can be run using Borland's TURBO C 2.0 compiler, the Microsoft C compiler (5.0), or compatible compilers.
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Add this copy of Neural Networks: an Introduction (Physics of Neural to cart. $102.81, new condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Santa Clarita, CA, UNITED STATES, published 1990 by Springer.
