Artificial Neural Networks |
UNIT I |
Introduction to Neural Networks – Basic Concepts of Neural Networks
– Inference and Learning – Classification Models – Association Models –
Optimization Models – Self-Organization Models. |
UNIT II |
Supervised and Unsupervised Learning – Statistical Learning – AI
Learning – Neural Network Learning – Rule Based Neural Networks – Network
Training – Network Revision- Issues- Theory of Revision- Decision Tree Based
NN – Constraint Based NN |
UNIT III |
Incremental learning – Mathematical Modeling – Application of NNKnowledge
based Approaches. |
UNIT IV |
Heuristics- Hierarchical Models – Hybrid Models – Parallel Models –
Differentiation Models- Control Networks – Symbolic Methods- NN Methods. |
UNIT V |
Structures and Sequences – Spatio-temporal NN – Learning Procedures
– Knowledge based Approaches. |
Text Books |
(i) L. Fu, 1994, Neural Networks in Computer Intelligence, Tata McGraw Hill, New
Delhi. |
Reference Books |
(i) R. J. Schalkoff, 1997, Artificial Neural Networks, Tata McGraw Hill, New Delhi.
(ii) Anderson, 2001, An Introduction to Neural Network, PHI, New Delhi. |