Table of Content

1. Introduction
2. Simple Neural Nets for Pattern Classification
3. Pattern Association
4. Neural Networks Based on Competition
5. Adaptive Resonance Theory
6. Backpropagation Neural Net
7. A Sampler of Other Neural Nets

Salient Features

• 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.