Structure level adaptation for artificial neural networks

1 Introduction.- 1.1 Background.- 1.2 Neural Network Paradigms.- 1.3 The Frame Problem in Artificial Neural Networks.- 1.4 Approach.- 1.5 Overview of This Book.- 2 Basic Framework.- 2.1 Introduction.- 2.2 Formal Neurons.- 2.3 Formal Neural Networks.- 2.4 Multi-Level Adaptation Formalism.- 2.5 Activity-Based Structural Adaptation.- 2.5.1 Neuron generation.- 2.5.2 Neuron Annihilation.- 2.5.3 Structural Relationship Modification.- 2.6 Summary.- 3 Multi-Layer Feed-Forward Networks.- 3.1 Introduction.- 3.2 Function Level Adaptation.- 3.3 Parameter Level Adaptation.- 3.4 Structure Level Adaptation.- 3.4.1 Neuron Generation.- 3.4.2 Neuron Annihilation.- 3.5 Implementation.- 3.6 An Illustrative Example.- 3.7 Summary.- 4 Competitive Signal Clustering Networks.- 4.1 Introduction.- 4.2 Basic Structure.- 4.3 Function Level Adaptation.- 4.4 Parameter Level Adaptation.- 4.5 Structure Level Adaptation.- 4.5.1 Neuron Generation Process.- 4.5.2 Neuron Annihilation and Coalition Process.- 4.5.3 Structural Relation Adjustment.- 4.6 Implementation.- 4.7 Simulation Results.- 4.8 Summary.- 5 Application Example: An Adaptive Neural Network Source Coder.- 5.1 Introduction.- 5.2 Vector Quantization Problem.- 5.3 VQ Using Neural Network Paradigms.- 5.3.1 Basic Properties.- 5.3.2 Fast Codebook Search Procedure.- 5.3.3 Path Coding Method.- 5.3.4 Performance Comparison.- 5.3.5 Adaptive SPAN Coder/Decoder.- 5.4 Summary.- 6 Conclusions.- 6.1 Contributions.- 6.2 Recommendations.