Fundamentals Of Neural Networks
By: Laurene Fausett
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Covers all major neural networks.
shows architectures in a similar format for all nets illustrating the similarities and differences among them.
Clarifies the differences in the capabilities of the different networks by focusing on simple problems in many cases variations of a theme.
Presents algorithms in enough detail to facilitate the writing of computer programs.
Gives detailed examples of simple applications.
Provides mathematical development when it provides a guide to proper implementation of a net.
Includes exercises and 25 computer projects.
Table of Contents
Simple Neural Nets for Pattern Classification
Neural Networks Based on Competition
Adaptive Resonance Theory
Backpropagation Neural Net
A Sampler of Other Neural Nets
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