1. Pattern Similarity and Storage Capacity of Hopfield Network Suman K Manandhar Prof. Ramakoti Sadananda Computer Science and Information Management AIT

2. Neural Networks To understand the nature To solve practical problems – Engineering.

3. Some Paradigms Perceptron – McCulloch-Pitts Multi layer networks – back propagation algorithms. Self-organizing maps Hopfield networks – recurrent networks

4. Hopfield Model Simple ON/OFF nodes connected by a weight matrix W Has pattern recognition and error correction properties

5. Dynamical Systems Basins of attraction – Fixed points Limit Cycles

6. OCR Applications

7. Grid Representation

8. Capacities This indicates the number of distinct patterns a network can hold

9. Patterns with Low Dh Similar patterns

10. Effect of Noise Such patterns become indistinguishable after noise corruption

11. Internet as Dynamic System A highly interconnected system where every node is independently operating. Self-Organization OR Chaos

12. COMPLEXITY SYSTEMSSELF-ORGANIZATION CHAOS