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DECEMBER 2015 P/PAN 16215/ PIEB 

Time : Three hours Maximum : 75 marks

PART A — (5 × 5 = 25 marks)

 Answer ALL questions.

1. (a) Define neural network. How will you define

the Boolean function in ANN?

Or

(b) Write short note on self-organization models.

2. (a) What is meant by NN learning? How will you

train NN learning?

Or

(b) Discuss about unsupervised learning.

3. (a) What are the constraints of incremental

modeling? Discuss.

Or

(b) How will you define mathematical modeling?

Give with example.

4. (a) State the heuristics in artificial neural

networks.

Or

(b) Discuss about symbolic methods in ANN.

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  P/PAN 16215/PIEB 2

5. (a) What is a spatio temporal NN? Mention the

constraints.

Or

(b) How will you define sequence in neural

networks? Discuss.

PART B — (5  10 = 50 marks)

 Answer any FIVE questions.

6. Describe the basic concepts of neural networks.

7. Compare inference with learning in neural

networks.

8. Explain in detail about decision tree based NN.

9. Discuss about network revision.

10. Write short note on ART1 networks and ART 2

network.

11. Explain in detail about differentiation models.

12. Discuss about any four learning procedure in

neural networks.

13. Explain the simulated annealing for stochastic

neural networks.

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