Intelligent Systems

Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system behavior. Fuzzy systems have similar applications. Their main advantage is their simplicity and ease of implementation. Various aspects of neural networks and fuzzy systems are covered in this volume from The Industrial Electronics Handbook, Second Edition. System optimization is also examined and several new techniques are discussed, including evolutionary methods and swarm and ant colony optimizations. The last section is devoted to several applications involving methods of computational intelligence.

Preface
Acknowledgements
Editorial Board
Editors
Contributors

Part I : Introductions
Chapter 1 : Introduction to Intelligent Systems
Chapter 2 : From Backpropagation to Neurocontrol
Chapter 3 : Neural Network-Based Control
Chapter 4 : Fuzzy Logic-Based Control Section
 
Part II : Neural Networks
Chapter 5 : Understanding Neural Networks
Chapter 6 : Neural Network Architectures
Chapter 7 : Radial-Basis-Function Networks
Chapter 8 : GMDH Neural Networks
Chapter 9 : Optimization of Neural Network Architectures
Chapter 10 : Parity-N Problems as a Vehicle to Compare Efficiencies of Neural Network Architectures
Chapter 11 : Neural Networks Learning
Chapter 12 : Levenberg-Marquardt Training
Chapter 13 : NBN Algorithm
Chapter 14 : Accelerating the Multilayer Perceptron Learning Algorithms
Chapter 15 : Feedforward Neural Networks Pruning Algorithms
Chapter 16 : Principal Component Analysis
Chapter 17 : Adaptive Critic Neural Network Control
Chapter 18 : Self-Organizing Maps

Part III : Fuzzy Systems
Chapter 19 : Fuzzy Logic Controllers
Chapter 20 : Neuro-Fuzzy System
Chapter 21 : Introduction to Type-2 Fuzzy Logic Controllers
Chapter 22 : Fuzzy Pattern Recognition
Chapter 23 : Fuzzy Modeling of Animal Behavior and Biomimcry : The Fuzzy Ant

Part IV : Optimizations
Chapter 24 : Multiobjective Optimization Methods
Chapter 25 : Fundamentals of Evolutionary Multiobjective Optimization
Chapter 26 : Ant Colony Optimization
Chapter 27 : Heuristics for Two-Dimensional Bin-Packing Problems
Chapter 28 : Practicle Swarm Optimization

Part V : Applications
Chapter 29 : Evolutionary Computation
Chapter 30 : Data Mining
Chapter 31 : Autonomous Mental Development
Chapter 32 : Synthetic Biometrics for Testing Biometric Systems and User Training

Index

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