This guide to neural networks includes worked problems in each chapter, and supporting software demonstrations. The authors of this work also developed the neural networks toolbox (for MathWorks) and the fuzzy systems toolbox (for PWS).
Neural Networks Summary
Neural Networks by Howard B. Demuth
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Table of Contents
Neuron model and network architectures; an illustrative examples; perceptron learning rule; signal and weight vector spaces; linear transformations for neural networks; supervised Hebbian learning; performance surfaces and optimum points; performance optimization; Widrow-Hoff learning.
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