Lecture 1 - Introduction to Intelligent Systems and Control
Lecture 2 - Linear Neural networks
Lecture 3 - Multi layered Neural Networks
Lecture 4 - Back Propagation Algorithm revisited
Lecture 5 - Non Linear System Analysis - Part I
Lecture 6 - Non Linear System Analysis - Part II
Lecture 7 - Radial Basis Function Networks
Lecture 8 - Adaptive Learning rate
Lecture 9 - Weight update rules
Lecture 10 - Recurrent networks Back propagation through time
Lecture 11 - Recurrent networks Real time recurrent learning
Lecture 12 - Self organizing Map - Multidimensional networks
Lecture 13 - Fuzzy sets - A Primer
Lecture 14 - Fuzzy Relations
Lecture 15 - Fuzzy Rule base and Approximate Reasoning
Lecture 16 - Introduction to Fuzzy Logic Control
Lecture 17 - Neural Control A review
Lecture 18 - Network inversion and Control
Lecture 19 - Neural Model of a Robot manipulator
Lecture 20 - Indirect Adaptive Control of a Robot manipulator
Lecture 21 - Adaptive neural control for Affine Systems SISO
Lecture 22 - Adaptive neural control for Affine systems MIMO
Lecture 23 - Visual Motor Coordination with KSOM
Lecture 24 - Visual Motor coordination - quantum clustering
Lecture 25 - Direct Adaptive control of Manipulators - Intro
Lecture 26 - NN based back stepping control
Lecture 27 - Fuzzy Control - a Review
Lecture 28 - Mamdani type flc and parameter optimization
Lecture 29 - Fuzzy Control of a pH reactor
Lecture 30 - Fuzzy Lyapunov controller - Computing with words
Lecture 31 - Controller Design for a T-S Fuzzy model
Lecture 32 - Linear controllers using T-S fuzzy model
