Information Theoretic Aspects of Neural Networks Book

Ch. 1	Introduction
1.1	Neuroinformatics	2
1.2	Information-Theoretic Framework of Neural Networks	15
1.3	Entropy, Thermodynamics and Information Theory	20
1.4	Information-Theoretics and Neural Network Training	22
1.5	Dynamics of Neural Learning in the Information- Theoretic Plane	38
1.6	Neural Nonlinear Activity in the Information- Theoretic Plane	40
1.7	Degree of Neural Complexity and Maximum Entropy	41
Ch. 2	Neural Complex: A Nonlinear C[superscript 3]I System?
2.1	Introduction	71
2.2	Neural Information Processing: C[superscript 3]I Protocols	72
2.3	Nonlinear Neural Activity	76
2.4	Bernoulli-Riccati Equations	80
2.5	Nonlinear Neural Activity: Practical Considerations	83
2.6	Entropy/Information Across a Neural Nonlinear Process	88
2.7	Nonsigmoidal Activation Functions	88
2.8	Definitions and Lemmas on Certain Classes of Nonlinear Functions	89
Ch. 3	Nonlinear and Informatic Aspects of Fuzzy Neural Activity
3.1	Introduction	113
3.2	What is Fuzzy Activity?	113
3.3	Crisp Set versus Fuzzy Sets	115
3.4	Membership Attributes to a Fuzzy Set	116
3.5	Fuzzy Neural Activity	119
3.6	Fuzzy Differential Equations	120
3.7	Membership Attributions to Fuzzy Sets via Activation Function	126
3.8	Neural Architecture with a Fuzzy Sigmoid	130
3.9	Fuzzy Considerations, Uncertainty and Information	134
3.10	Information-Theoretics of Crisp and Fuzzy Sets	135
3.11	Fuzzy Neuroinformatics	141