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Table of Contents
Introduction
Part I: Neural Networks
Introduction
Threshold Logic Units
General Neural Networks
Multi-Layer Perceptrons
Radial Basis Function Networks
Self-Organizing Maps
Hopfield Networks
Recurrent Networks
Mathematical Remarks for Neural Networks
Part II: Evolutionary Algorithms
Introduction to Evolutionary Algorithms
Elements of Evolutionary Algorithms
Fundamental Evolutionary Algorithms
Computational Swarm Intelligence
Part III: Fuzzy Systems
Fuzzy Sets and Fuzzy Logic
The Extension Principle
Fuzzy Relations
Similarity Relations
Fuzzy Control
Fuzzy Data Analysis
Part IV: Bayes and Markov Networks
Introduction to Bayes Networks
Elements of Probability and Graph Theory
Decompositions
Evidence Propagation
Learning Graphical Models
Belief Revision
Decision Graphs.
Part I: Neural Networks
Introduction
Threshold Logic Units
General Neural Networks
Multi-Layer Perceptrons
Radial Basis Function Networks
Self-Organizing Maps
Hopfield Networks
Recurrent Networks
Mathematical Remarks for Neural Networks
Part II: Evolutionary Algorithms
Introduction to Evolutionary Algorithms
Elements of Evolutionary Algorithms
Fundamental Evolutionary Algorithms
Computational Swarm Intelligence
Part III: Fuzzy Systems
Fuzzy Sets and Fuzzy Logic
The Extension Principle
Fuzzy Relations
Similarity Relations
Fuzzy Control
Fuzzy Data Analysis
Part IV: Bayes and Markov Networks
Introduction to Bayes Networks
Elements of Probability and Graph Theory
Decompositions
Evidence Propagation
Learning Graphical Models
Belief Revision
Decision Graphs.