Static and dynamic neural networks : from fundamentals to advanced theory / Madan M. Gupta, Liang Jin, Noriyasu Homma.
Material type: TextPublisher: [Hoboken, New Jersey] : Wiley, 2003Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2005]Description: 1 PDF (xxviii, 722 pages) : illustrationsContent type:- text
- electronic
- online resource
- "A classified extended bibliography is listed in Appendix B on the following ftp site: ftp://ftp.wiley.com/public/sci_tech_med/neural_networks/"
- 9780471427957
- 006.3/2
Includes bibliographical references and index.
Foreword: Lotfi A. Zadeh. -- Preface. -- Acknowledgments. -- PART I: FOUNDATIONS OF NEURAL NETWORKS. -- Neural Systems: An Introduction. -- Biological Foundations of Neuronal Morphology. -- Neural Units: Concepts, Models, and Learning. -- PART II: STATIC NEURAL NETWORKS. -- Multilayered Feedforward Neural Networks (MFNNs) and Backpropagation Learning Algorithms. -- Advanced Methods for Learning Adaptation in MFNNs. -- Radial Basis Function Neural Networks. -- Function Approximation Using Feedforward Neural Networks. -- PART III: DYNAMIC NEURAL NETWORKS. -- Dynamic Neural Units (DNUs): Nonlinear Models and Dynamics. -- Continuous-Time Dynamic Neural Networks. -- Learning and Adaptation in Dynamic Neural Networks. -- Stability of Continuous-Time Dynamic Neural Networks. -- Discrete-Time Dynamic Neural Networks and Their Stability. -- PART IV: SOME ADVANCED TOPICS IN NEURAL NETWORKS. -- Binary Neural Networks. -- Feedback Binary Associative Memories. -- Fuzzy Sets and Fuzzy Neural Networks. -- References and Bibliography. -- Appendix A: Current Bibliographic Sources on Neural Networks. -- Index.
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Provides comprehensive treatment of the theory of both static and dynamic neural networks. * Theoretical concepts are illustrated by reference to practical examples Includes end-of-chapter exercises and end-of-chapter exercises. *An Instructor Support FTP site is available from the Wiley editorial department.
Also available in print.
Mode of access: World Wide Web
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