Sunday, June 24, 2018

Neural Network design by Hagan, Demuth and Beale

Neural Network design by Hagan, Demuth and Beale

This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems. Features Extensive coverage of training methods for both feedforward networks (including multilayer and radial basis networks) and recurrent networks. In addition to conjugate gradient and Levenberg-Marquardt variations of the backpropagation algorithm, the text also covers Bayesian regularization and early stopping, which ensure the generalization ability of trained networks. 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, along with five chapters presenting detailed real-world case studies

Product details

Paperback: 800 pages

Publisher: Martin Hagan; 2 edition (September 1, 2014)

Language: English

ISBN-10: 0971732116

ISBN-13: 978-0971732117

Product Dimensions: 7.5 x 1.8 x 9.2 inches


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