{"product_id":"9783540602071","title":"Neural Networks, w. diskette (3 1\/2 inch) : An Introduction (Physics of Neural Networks) (2nd ed. 1995. 300 p. w. 83 figs. 24,5 cm)","description":"\u003cb\u003eNeural Networks \u003c\/b\u003epresents 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 Optimization.- 12. VLSI and Neural Networks.- 13. Symmetrical Networks with Hidden Neurons.- 14. Coupled Neural Networks.- 15. Unsupervised Learning.- 16. Evolutionary Algorithms for Learning.- 17. Statistical Physics and Spin Glasses.- 18. The Hopfield Network for p\/N' 0.- 19. The Hopfield Network for Finite p\/N.- 20. The Space of Interactions in Neural Networks.- 21. Numerical Demonstrations.- 22. ASSO: Associative Memory.- 23. ASSCOUNT: Associative Memory for Time Sequences.- 24. PERBOOL: Learning Boolean Functions with Back-Prop.- 25. PERFUNC: Learning Continuous Functions with Back-Prop.- 26. Solution of the Traveling-Salesman Problem.- 27. KOHOMAP: The Kohonen Self-organizing Map.- 28. btt: Back-Propagation Through Time.- 29. NEUROGEN: Using Genetic Algorithms to Train Networks.- References. \"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","brand":"SPRINGER, BERLIN","offers":[{"title":"Default Title","offer_id":48761608700139,"sku":"00000_00000_00000_00000","price":100.69,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0758\/4484\/5803\/files\/9783540602071-1.jpg?v=1781723375","url":"https:\/\/kinokuniya.com.sg\/ja\/products\/9783540602071","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}