| NEURAL NETWORKS AND FUZZY LOGIC |
| PAPER NO. 2 |
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| PUT ON: Dec 2002 |
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EC - 44 NEURAL NETWORKS AND FUZZY LOGIC (B.Tech 8th Semester, 2122) Time : 3 Hours Maximum Marks : 60 NOTE:- This paper consist of Three Sections. Section A is compulsory. Do any Four questions from Section B and any two questions from Section C Section-A Marks : 20 1(a) Define synaptic strength. (b) What is the difference between fuzzyfication and discretization ? Give at least one example for each. (c) What is delta rule ? (d) What is the basic principal behind Neural Metwork ? (e) Why we use activation functions in Neural Network ? (f) Why are neurons so slow ? (g) What is the role of membership function ? (h) What can you do with Neural Network ? (i) Why do we use bias input ? (j) Define assosiative memory. Section-B Marks:5 Each 2. Why single layer perception has limited capability as compared to multilayer ? Explain it. 3. Explain basic fuzzy interence algorithm. 4. Discuss the applications of Neural Network in Decision-making. 5. Compare the performance of biological and computer Neural Network. 6. What do you mean by vector quantization ? How Neural Network is helpful for this application ? Section-C Marks : 10 Each 7. Discuss the model of ART Network. 8. Explain the applicaion of fuzzy logic. 9. Write short notes on the following : (a) Correlation learning law. (b) Outstar learning rules. (c) Radial basis function. |
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