SC mid exam syllabus

 Mid Sem Exam Syllabus 

Sem - VII                                Subject- Soft Computing

Neural Networks :Supervised Learning Neural Networks – Perceptrons -Adaline – Back propagation Multilayer Perceptrons – Radial Basis Function Networks – Unsupervised Learning Neural Networks – CompetitiveLearning Networks – Kohonen Self-Organizing Networks -Learning Vector Quantization – Hebbian Learning.

Fuzzy Set Theory :

Introduction to Neuro – Fuzzy and Soft Computing –

Fuzzy Sets – Basic Definition and Terminology – Set-theoretic Operations – Member Function

Formulation and Parameterization – Fuzzy Rules and

Fuzzy Reasoning – Extension Principle and Fuzzy Relations – Fuzzy If-Then Rules – Fuzzy

Reasoning – Fuzzy Inference Systems MamdaniFuzzy

Models – Sugeno Fuzzy Models – Tsukamoto Fuzzy Models – Input SpacePartitioning and FuzzyModeling.

 

Rough Set:

Indiscernibility Relations, Reducts, Rough Approximation. Applications. Hybrid Systems: Neuro Fuzzy Systems, Fuzzy Logic Controlled GA, Fuzzy Membership Interpretation using Rough Set theory etc.