Neural Networks and Learning Machines. 3rd Ed. Simon O. Haykins. Pearson. 2008

Chapter 8. Principal-Components Analysis

8.1 Introduction

8.2 Principles of Self-Organization

Principle 1. Self-Amplification

Principle 2. Competition

Principle 3. Cooperation

Principle 4. Structural Information

8.3 Self-Organized Feature Analysis

8.4 Principal-Components Analysis: Perturbation Theory

8.5 Hebbian-Based maximum Eigenfilter

8.6 Hebbian-Based Principal Components Analysis

8.7 Case Study: Image Coding

8.8 Kernel Principal-Components Analysis

8.9 Basic Issues Involved in the Coding of Natural Images

8.10 Kernel Hebbian Algorithm

8.11 Summary and Discussion

Chapter 9. Self-Organizing Maps


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