Table of Contents

1. Introduction 2. Neural Networks: An Overview 3. Preprocessing 4. Feed-Forward Networks with Supervised Learning 5. Some Other Types of Neural Networks 6. Feature Extraction I: Geometric Features and Transformations 7. Feature Extraction II: Principal Component Analysis 8. Kohonen Networks and Learning Vector Quantization 9. Neural Associative Memories and Hopfield Networks 10. Adaptive Resonance Theory (ART) 11. Neocognitron 12. Systems with Multiple Classifiers

About the Author

Pandya, Abhijit S.; Macy, Robert B.