- Category: Computer
- Author: Martin T. Hagan
- Pages: 800 pages
- File type: PDF (1012 pages, 11 MB)
Read and download free eBook intituled Neural Network Design in format PDF (1012 pages, 11 MB) – 800 pages created by Martin T. Hagan.
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.
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