CBCGS [2019 - current]

CBGS [2015 - 2018]

Old [2000 - 2014]

## Topics with syllabus and resources

100.00 Introduction to Soft Computing

- Soft computing Constituents, Characteristics of Neuro Computing and Soft Computing, Difference between Hard Computing and Soft Computing, Concepts of Learning and Adaptation.

200.00 Neural Networks

201.00 Basics of Neural Networks

- Introduction to Neural Networks, Biological Neural Networks, McCulloch Pitt model.

202.00 Supervised Learning Algorithms

- Perceptron (Single Layer, Multi layer), Linear separability, Delta learning rule, Back Propagation algorithm.

203.00 Un-supervised Learning Algorithms

- Hebbian Learning, Winner take all, Self Organizing Maps, Learning Vector Quantization.

300.00 Fuzzy Set Theory

- Classical Sets and Fuzzy Sets, Classical Relations and Fuzzy Relations, Properties of membership function, Fuzzy extension principle, Fuzzy Systems- fuzzification, defuzzification and fuzzy controllers.

400.00 Hybrid System

- Introduction to Hybrid Systems, Adaptive Neuro Fuzzy Inference System (ANFIS).

500.00 Introduction to Optimization Techniques

- Derivative based optimization- Steepest Descent, Newton method.
- Derivative free optimization- Introduction to Evolutionary Concepts.

600.00 Genetic Algorithms and Its Applications

- Inheritance Operators, Cross over types, inversion and Deletion, Mutation Operator, Bit-wise Operators, Convergence of GA, Applications of GA.