Electrical Engineering, University of Kansas has taught and conducted research in the areas of control systems and signal processing for the last 35 years. Neural Network Design — Martin T. Hagan, Howard B. Demuth, Mark H.
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Hagan, Howard B. Demuth, Mark H. In it, the authors emphasize a fundamental understanding of the principal neural networks and the methods for training them. The authors also discuss applications of networks to practical engineering problems in pattern recognition, clustering, signal processing, and control systems.
Readability and natural flow of material is emphasized throughout the text. Features Extensive coverage of performance learning, including the Widrow-Hoff rule, backpropagation and several enhancements of backpropagation, such as the conjugate gradient and Levenberg-Marquardt variations.
Both feedforward network including multilayer and radial basis networks and recurrent network training are covered in detail. The text also covers Bayesian regularization and early stopping training methods, which ensure network generalization ability. Associative and competitive networks, including feature maps and learning vector quantization, are explained with simple building blocks. A chapter of practical training tips for function approximation, pattern recognition, clustering and prediction applications is included, along with five chapters presenting detailed real-world case studies.
Detailed examples, numerous solved problems and comprehensive demonstration software. New in the 2nd Edition The 2nd edition contains new chapters on Generalization, Dynamic Networks, Radial Basis Networks, Practical Training Issues, as well as five new chapters on real-world case studies. In addition, a large number of new homework problems have been added to each chapter. Obtaining the Book A free page eBook version of the book A somewhat condensed page paperback edition of the book can be ordered from Amazon.
Related Resources Transparency Masters The numbering of chapters in the transparency masters follows the eBook version of the text. Transparency Masters Data for Case Studies.
HAGAN DEMUTH BEALE NEURAL NETWORK DESIGN PDF