Courses in the Fourth Semester

MMTE-007 Soft Computing and Its Applications (4 Credits)


“Soft Computing and its Applications” is a 4-credit course. This course involves theory component as well as practical component. In this course the three main components of soft computing, fuzzy logic, neural networks and genetic algorithms are discussed with applications. The prerequisite dependency for this course is “Probability and Statistics”, (MMT-008) which you would have studied during the second semester of the programme. This course comprises four blocks related to soft computing. It begins with fuzzy set, and fuzzy C-mean algorithm in Block 1. The next two blocks discuss neural network with its applications. In the last block, the course concludes with several genetic algorithms. The practical assignments are listed at the end of corresponding unit.

Block 1 Fuzzy Sets


Unit 1 Fuzzy Set - An Introduction


Unit-1.pdf



Unit 2 Fuzzy Clustering



Unit-2.pdf



Unit 3 Fuzzy Pattern Recognition



Unit-3.pdf


Block 2 Neural Networks I


Unit 4 Fundamentals of Neural Networks

Unit-4.pdf



Unit 5 Single Layer Perceptrons

Unit-5.pdf


Unit 6 Multi Layer Perceptrons

Unit-6.pdf

Block 3 Neural Networks II



Unit 7 Applications of MLP



Unit-7.pdf



Unit 8 Radial Basis Function Networks



Unit-8.pdf



Unit 9 Hopfield Networks



Unit-9.pdf



Unit 10 Kohonen Networks



Unit-10.pdf


Block 4 Genetic Algorithm (GA)


Unit 11 Simple Genetic Algorithm

Unit-11.pdf



Unit 12 Applications of Genetic Algorithm

Unit-12.pdf



Unit 13 The Schema Theorem

Unit-13.pdf