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Course Detail

Course Name Introduction to Soft Computing
Course Code 15ECE368
Program B. Tech. in Electronics and Communication Engineering
Year Taught 2019


Unit 1

Overview of Artificial Neural Networks (ANN) – Models of a neuron – Network architectures – Bayes theorem – Naïve Bayes classifier – Rosenblatt’s Perceptron – Perceptron convergence theorem – Multilayer Perceptrons – Back propagation – Application of ANN in Classification and Regression – Classifier performance measures – Validation techniques.

Unit 2

Fundamentals of Genetic Algorithms – Creation of offspring – Encoding – Fitness function – Reproduction – Inheritance operators – Crossover – Inversion and deletion – Mutation – Generational cycle – Convergence of GA – Applications.

Unit 3

Introduction to basic Particle Swarm Optimization (PSO) algorithm – Swarm size – Information links – Initialization – Equations of motion – Interval confinement – Proximity distributions – Applications

Text Books

  1. Simon Haykin, “Neural Networks & Learning Machines”, PHI Learning Pvt. Ltd – New Delhi, Third Edition, 2010.
  2. Clerc, Maurice, “Particle swarm optimization”, John Wiley & Sons, 2010.


  • Anil K. Jain, “Fundamentals of digital image processing” Prentice Hall of India Private Limited, 1996.

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