Syllabus - ARTIFICIAL NEURAL NETWORKS (BM-704)

Practicals based on experimental setups or coding/simulation mode on the following topics

1. Parallel and distributed processing - I: Interactive activation and competition models 2. Parallel and distributed processing - II: Constraint satisfaction neural network models 3. Perceptron learning 4. Multilayer feed forward neural networks 5. Hopfield model for pattern storage task 6. Hopfield model with stochastic update 7. Competitive learning neural networks for pattern clustering 8. Solution to travelling salesman problem using self organizing maps 9. Solution to optimization problems using Hopfield models 10. Weighted matching problem: Deterministic, stochastic and mean-field annealing of an Hopfield model