IT804

Course Name: 

Artificial Neural Networks (IT804)

Programme: 

M.Tech (IT)

Category: 

Elective Courses (Ele)

Credits (L-T-P): 

(3-0-0) 3

Content: 

Introduction to Artificial Neural Networks , Artificial Neuron Model and Linear Regression, Gradient Descent Algorithm, Nonlinear Activation Units and Learning Mechanisms,
Associative Memory Model, Statistical Aspects of Learning, Single-Layer Perceptions, Least Mean Squares Algorithm, Perceptron Convergence Theorem, Bayes Classifier, Back
Propagation Algorithm, Multi-Class Classification Using Multi- layered Perceptrons, Radial Basis Function Network, Principal Component Analysis and Independent Component Analysis, Self Organizing Maps, Applications and Recent Research Trends.

References: 

Simon Haykin, “Neural networks - A comprehensive foundations”, Pearson, 2004.
Laurene Fausett: “Fundamentals of neural networks: architectures, algorithms, and applications”,Prentice Hall.
J A. Freeman, D M. Skapure: Neural Networks Algorithms, Applications & Programming Techniques, Addison-Wesley.
James A. Anderson, “An Introduction to Neural Networks”, Prentice Hall of India.
Yegnanarayana: “Artificial Neural Networks”, Prentice Hall of India, 2004.

Department: 

Information Technology
 

Contact us

G. Ram Mohana Reddy

Professor and Head,
Department of Information Technology, NITK, Surathkal,
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.
Ph.:    +91-824-2474056
Email:  infotech[AT]nitk[DOT]ac[DOT]in
            infotech[AT]nitk[DOT]edu[DOT]in

Sowmya Kamath S (Web Admin)

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