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Neural Networks 2nd Edition
Neural Networks provides a gentle introduction to the subject, for undergraduates from computer science and electrical engineering degrees. This updated and revised second edition assumes no prior knowledge and sets out to describe what neural nets are, what they do, and how they do it. The main networks covered include ADALINE, WISARD, the Hopfield
Network, Bidirectional Associative Memory, the Boltzmann machine, counter propogation and ART networks, and Kohonen's self organizing maps. These networks are discussed by means of examples, giving the reader an overall knowledge of current developments in the field.
Contents:
Preface - What is a Neural Network - ADALINE - Perceptrons - Boolean Neural Networks - Associative Memory and Feedback Networks - Statistical Neural Networks - Self-organizing Networks - Neural Networks in Control Engineering - Multi-Layered Perceptron - Threshold Logic - Implementation - Conclusions - References - Appendix A - Derivation of the Delta Rule
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