Course Title: 
Soft Computing Techniques
Course Code: 
Year Taught: 
Postgraduate (PG)
School of Arts and Sciences

'Soft Computing Techniques' is an elective course offered in the M. Phil. in Computer Science & IT (Part time) at School of Arts and Science, Amrita Vishwa Vidyapeetham.  

Unit I:

Artificial Intelligence – a Brief Review – Pitfalls of Traditional AI – Need for Computational Intelligence – Importance of Tolerance of Imprecision and Uncertainty - Constituent Techniques – Overview of Artificial Neural Networks - Fuzzy Logic - Evolutionary Computation.

Unit II:

Neural Network: Biological and Artificial Neuron, Neural Networks, Supervised and Unsupervised Learning. Single Layer Perceptron - Multilayer Perceptron – Backpropagation Learning.

Unit III:

Neural Networks as Associative Memories - Hopfield Networks, Bidirectional Associative Memory. Topologically Organized Neural Networks – Competitive Learning, Kohonen Maps,

Unit IV:

Fuzzy Logic: Fuzzy Sets – Properties – Membership Functions - Fuzzy Operations. Fuzzy Logic and Fuzzy Inference System

Unit V:

Evolutionary Computation - Overview of other Bio-inspired Algorithms - Swarm Intelligence Algorithms

  1. Kumar S., “Neural Networks - A Classroom Approach”, Tata McGraw Hill, 2004.
  2. Ross T. J., “Fuzzy Logic with Engineering Applications”, McGraw Hill, 1997.
  3. Eiben A. E. and Smith J. E., “Introduction to Evolutionary Computing”, Second Edition, Springer, Natural Computing Series, 2007.
  4. Engelbrecht A. P., “Fundamentals of Computational Swarm Intelligence”, John Wiley & Sons, 2006.
  5. Konar. A, “Computational Intelligence: Principles, Techniques and Applications”, Springer Verlag, 2005.