Static and Dynamic Neural Networks

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.

Provides comprehensive treatment of the theory of both static anddynamic neural networks.* Theoretical concepts are illustrated by reference to practicalexamples Includes end-of-chapter exercises and end-of-chapterexercises.*An Instructor Support FTP site is available from the Wileyeditorial department.

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) andBackpropagation 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 NeuralNetworks.Index.