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- catalog abstract ""This book represents the most comprehensive treatment available of neural networks from an engineering perspective. Thorough, well-organized, and completely up to date, it examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks." "Written in a concise and fluid manner, by a foremost engineering textbook author, to make the material more accessible, this book is ideal for professional engineers and graduate students entering this exciting field. Computer experiments, problems, worked examples, a bibliography, photographs, and illustrations reinforce key concepts."--Jacket.".
- catalog contributor b7324591.
- catalog created "c1994.".
- catalog date "1994".
- catalog date "c1994.".
- catalog dateCopyrighted "c1994.".
- catalog description ""This book represents the most comprehensive treatment available of neural networks from an engineering perspective. Thorough, well-organized, and completely up to date, it examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks." "Written in a concise and fluid manner, by a foremost engineering textbook author, to make the material more accessible, this book is ideal for professional engineers and graduate students entering this exciting field. Computer experiments, problems, worked examples, a bibliography, photographs, and illustrations reinforce key concepts."--Jacket.".
- catalog description "1. Introduction -- 2. Learning Process -- 3. Correlation Matrix Memory -- 4. Perceptron -- 5. Least-Mean-Square Algorithm -- 6. Multilayer Perceptrons -- 7. Radial-Basis Function Networks -- 8. Recurrent Networks Rooted in Statistical Physics -- 9. Self-Organizing Systems I: Hebbian Learning -- 10. Self-Organizing Systems II: Competitive Learning -- 11. Self-Organizing Systems III: Information-Theoretic Models -- 12. Modular Networks -- 13. Temporal Processing -- 14. Neurodynamics -- 15. VLSI Implementations of Neural Networks -- Appendix A: Pseudoinverse Matrix Memory -- Appendix B: A General Tool for Convergence Analysis of Stochastic Approximation Algorithms -- Appendix C: Statistical Thermodynamics -- Appendix D: Fokker-Planck Equation.".
- catalog description "Includes bibliographical references (p. 635-690) and index.".
- catalog extent "xix, 696 p. :".
- catalog hasFormat "Neural networks.".
- catalog identifier "0023527617".
- catalog isFormatOf "Neural networks.".
- catalog issued "1994".
- catalog issued "c1994.".
- catalog language "eng".
- catalog publisher "New York : Macmillan ; Toronto : Maxwell Macmillan Canada ; New York : Maxwell Macmillan International,".
- catalog relation "Neural networks.".
- catalog subject "006.3 20".
- catalog subject "Neural networks (Computer science)".
- catalog subject "QA76.87 .H39 1994".
- catalog tableOfContents "1. Introduction -- 2. Learning Process -- 3. Correlation Matrix Memory -- 4. Perceptron -- 5. Least-Mean-Square Algorithm -- 6. Multilayer Perceptrons -- 7. Radial-Basis Function Networks -- 8. Recurrent Networks Rooted in Statistical Physics -- 9. Self-Organizing Systems I: Hebbian Learning -- 10. Self-Organizing Systems II: Competitive Learning -- 11. Self-Organizing Systems III: Information-Theoretic Models -- 12. Modular Networks -- 13. Temporal Processing -- 14. Neurodynamics -- 15. VLSI Implementations of Neural Networks -- Appendix A: Pseudoinverse Matrix Memory -- Appendix B: A General Tool for Convergence Analysis of Stochastic Approximation Algorithms -- Appendix C: Statistical Thermodynamics -- Appendix D: Fokker-Planck Equation.".
- catalog title "Neural networks : a comprehensive foundation / Simon Haykin.".
- catalog type "text".