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

Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in
 

Web Admin: Sowmya Kamath S

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