CE835 Soft Computing

Course Name: 

CE835 Soft Computing


M.Tech (CE)


Elective (Ele)

Credits (L-T-P): 

(3–0–0 ) 3


Introduction to learning systems - Feed forward Neural Networks - Perception - Multilayer Perception. Propagation algorithm and its variants - Improving generalization by various methods. Recurrent Neural Networks Hopfield net Boltzmann machine and Mean field learning solving combinational optimization problems using recurrent Neural Networks. Unsupervised Neural Networks. Competitive learning Self-organizing maps Growing cell structures Principal component analysis. Basics of fuzzy sets. Genetic algorithms: Population based search techniques, evolutionary strategies, mathematical foundations of genetic algorithms, search operators, genetic algorithms in function and combinational optimization, hybrid algorithms, application to pattern recognition


S. Haykin, Neural Networks: A comprehensive foundation, Pearson, 1999
J. M. Zurada, Introduction to artificial neural networks, Jaico publishing, 1997.
B. Yejnanarayana, Artificial Neural Networks, PHI, 1999
C. Mohan and S. Ranka, Neural networks, Benram publications, 2004.

Contact us

Dr. U. Shripathi Acharya,  Professor and Head, 
Department of E&C, NITK, Surathkal
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

  • Hot line: +91-0824-2473046

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