Neural Networks An Introduction [Paperback]

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.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.1. The Structure of the Central Nervous System.- 2. Neural Networks Introduced.- 3. Associative Memory.- 4. Stochastic Neurons.- 5. Cybernetic Networks.- 6. Multilayered Perceptrons.- 7. Applications.- 8. More Applications of Neural Networks.- 9. Network Architecture and Generalization.- 10. Associative Memory: Advanced Learning Strategies.- 11. Combinatorial OptimizalÃq