YunTech elearning

1) Intelligent Control Introduction
A. What is Artificial Intelligence?
B. History and Theorem Introduction
C. Uncertain, Time Varying, and Nonlinear System
D. Feedback and Feedforward Control System
2) Fuzzy Set and Control Theorem
A. Cripsets & Fuzzy Sets 
B. Operation on Fuzzy sets
C. Fuzzy Relation
D. Fuzzy Dynamics System
E. Demystification of Fuzzy Control
F. Stability Issues of Fuzzy Logic Controlled Systems 
G. Sliding Mode Fuzzy Controllers 
H. Fuzzy Modeling
I. Adaptive Fuzzy Controllers 
3) Neural Networks Theorem
A. Introduction to Neurocomputing
B. Basic Models of Artificial Neurons 
C. Perceptron, Feedforward Multilayer Perceptron
D. Basic Learning Rules for a Single Neuron
E. Backpropagation Learning Algorithm
F. Radial-Basis Function Networks
G. Self-Organizing Networks
H. Recurrent Networks and Temporal Feedforward Networks
I. Hopfield Neural Networks
J. Applications 
4) Genetic Algorithm
A. Introduction 
B. Genetic Algorithm Operator
C. Components of a GA 
D. Problems Solved by GA
5) Learning Control Theorem
A. Introduction of Iterative Learning 
B. Quantization of Iterative Learning Behavior
C. Specification of Iterative Learning Control 
D. Performance Evaluation of Iterative Learning Control
E. Arimoto-type Learning Laws
F. The Design of Fuzzy Learning Controller
G. Analysis of Convergence
H. Iterative Learning via Sliding Hyperplanes
6) Practical Examples and Application Topics (Arranging)