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University of Madras (UoM)

University of Madras (UoM)

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Artificial Neural Network - Elective II
OCTOBER 2003
P/IC 16117/KSB

Time: Three hours
Maximum: 75 marks

PART A - (5 x 5 = 25 marks)

Answer ALL questions.
All questions carry equal marks.

1. (a) Explain the neural system hierarchies, with examples.

Or

(b) Describe self organisation model.

2. (a) Explain correlation based learning method.

Or

(b) What is a constraint based neural network? Discuss.

3. (a) Describe the incremental learning principle.

Or

(b) Explain error measures and error trajectories for ANN learning approaches.

4. (a) Discuss about control networks.

Or

(b) Explain hybrid models and compare with parallel models.

5. (a) What is spatio temporal neural network? Discuss.

Or

(b) What are symbolic schemes? Explain them.

PART B - (5 x 10 = 50 marks)

Answer any FIVE questions.
All questions carry equal marks.

6. Explain the basic concepts of neural networks.

7. Describe Back propagation network and explain how error is minimized.

8. Explain various learning schemes used in NN.

9. Describe mathematical modeling for learning procedure.

10. Explain the differentiation models for neural networks.

11. Discuss the significance of symbolic methods in NN.

12. Describe knowledge based approaches in learning and compare with other schemes.

13. Write short notes on:
(a) Optimization models
(b) Applications of neural networks.
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