EC 6010 / EC 6032 (o)

EC 6010( EC 6032 OLD)
Artificial Neural Networks and its Application

1. Network architecture, Artificial intelligence and neural networks, Learning processes, Learning with or without a teacher, Memory adoption, and statistical nature of learning process.
2. Single layer perception, Adaptive filtering problem, LMS Algorithm, Learning curve, Perception convergence
3. Multi-layer perception: Back propagation, algorithm, output presentation and decision rule, supervised learning as optimization problem, Generalized radial basics, Function network.
4. Temporal processing using feed forward network, Network Architectures, Distributed time lagged feed forward network, Temporal back propagation algorithm.
5. Dynamically driven recurrent networks, Sate space model, Learning algorithms, Real time recurrent learning, Kalman Filter, De-coupled extended kalman filters.

Books:

• Neural network- A Comprehensive foundation, 2nd Ed, Simon Haykin, Addison Wiseley Longman, New York, 2001.
• Neural Network- Algorithms, Applications and progggramming, J A Freeman and D M Skapura, AWL, NY, 2000.
• An introduction to Neural Network, James A Anderson, Prentice Hall of India, New Delhi.