CO542:Neural Networks and Fuzzy Systems
| Course Number : CO542 | ||||
|---|---|---|---|---|
| Course Title : Neural Networks and Fuzzy Systems | ||||
| Credits : 3 | ||||
| Prerequisites : None | ||||
| No | Course Content | Time Allocated (hours) | ||
| L&T | P&A | |||
| 01 | Introduction to Fuzzy Systems Fuzzy sets, membership functions, Fuzzy set operations, properties of fuzzy sets. |
1 |
|
|
| 02 | Fuzzy Relations Membership functions, Fuzzy relations, fuzzyfications, operations on fuzzy relations. |
2 | 2 |
|
| 03 | Extension Principle Fuzzy to crisp conversions, extension principle, fuzzy numbers, fuzzy vectors |
2 | 2 | |
| 04 | Fuzzy Inference Fuzzy reasoning, fuzzy inference, fuzzy rule based systems, design of rule based systems |
3 | 3 | |
| 05 | Fuzzy Non-linear Simulation Fuzzy non-linear simulation, fuzzy decision making, cluster analysis, fuzzy c-means |
3 | 3 | |
| 06 | Fuzzy Applications Fuzzy pattern recognition, fuzzy control systems. |
4 | 3 | |
| 07 | Artificial Neural Networks (ANN) Concepts, basic model of a neuron |
2 | ||
| 08 | Learning in ANN Supervised learning, unsupervised learning, reinforced learning, competitive learning, the delta rule, Hebbian learning, ANN adaptability. |
3 | ||
| 09 | The Perceptron Neural networks paradigms, perceptron, Adaline and Madaline models |
2 | ||
| 10 | Back Propagation Algorithm Learning with the back propagation, mathematical analysis, applications |
3 | 3 | |
| 11 | Hopefield Model Mathematical analysis, Hopefield learning algorithm, applications |
2 | 3 | |
| 12 | Memory Type Paradigms Bidirectional associative memory, temporal associative memory, linear associative memory, self organizing maps. |
3 | ||
| 13 | Fuzzy Neural Networks Applications |
3 | 5 | |
| Total |
33 | 24 | ||
| Assessment | Percentage Marks | |||
| Continuous Assessment | 30 | |||
| Class participation | 5 | |||
| Assignments / Practical | 25 | |||
| Written Examinations | 70 | |||
| Mid-Semester | 20 | |||
| End of Semester | 50 | |||