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