http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
1 online resource (xxviii, 722 pages) : illustrations
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.
Foreword; Preface; Acknowledgments; 1 Neural Systems: An Introduction; 2 Biological Foundations of Neuronal Morphology; 3 Neural Units: Concepts, Models, and Learning; 4 Multilayered Feedforward Neural Networks (MFNNs) and Backpropagation Learning Algorithms; 5 Advanced Methods for Learning and Adaptation in MFNNs; 6 Radial Basis Function Neural Networks; 7 Function Approximation Using Feedforward Neural Networks; 8 Dynamic Neural Units (DNUs): Nonlinear Models and Dynamics; 9 Continuous-Time Dynamic Neural Networks; 10 Learning and Adaptation in Dynamic Neural Networks.
Madan M. Gupta, Liang Jin, Noriyasu Homma.
Includes bibliographical references and index.
46264938-AEF8-488F-ABC8-C64B2A6EBB25 OverDrive, Inc.