SOFT COMPUTING (SC) [ELECTIVE], Semester 7, B.E. Computer Science (CS), May 2012.

SOFT COMPUTING (SC) [ELECTIVE], Semester 7,

B.E. Computer Science (CS), May 2012.

Con.4679-12

GN- 9047

(3 Hours)

[Total Mark: 100]

N.B. 1. Question No. 1 is compulsory.

2. Attempt any Four questions out of the remaining.

3. Figures to the right indicate full marks

1. (a) Explain fuzzy extension principle with the help of an example. --- (6 Marks)

(b) Explain Mc Culloch Pitts Neuron Model with help of an example. --- (6 Marks)

(c) Explain standard fuzzy membership functions. --- (8 Marks)

2. Design a Fuzzy logic controller for a domestic washing machine with two Inputs dirtiness of the load and weight of the laundry and output as amount of detergent used. Use five descriptors for each linguistic variable. Generate a set of rules for control action and defuzzification. ---- (20 Marks)

3. (a) What is learning in Neural Networks? Compare different learning rules. ---- (10 Marks)

(b) Explain error back propagation training algorithm with the help of a flowchart. ---- (10 Marks)

4. (a) Determine the weights after one iteration for hebbian learning of a single neuron network starting with initial weights W = [1, -1], inputs as ----- (12 Marks)

X1 = [1, -2], X2 = [2, 3], X3 = [1, -1] and c=1.

Use (i) Bipolar binary activation function

(ii) Bipolar continuous activation function

(b) Explain perceptron Learning with the help of an example. --- (8 Marks)

5. (a) Explain with examples linearly separable and non – linearly separable pattern classification. --- (10 Marks)

(b) Explain the three types of fuzzy Interface Systems in detail. --- (10 Marks)

6. (a) Explain Travelling Salesperson Problem using Simulated Annealing. ---- (10 Marks)

(b) Explain RBF network and give the comparison between RBF and MLP. --- (10 Marks)

7. Write notes on any two of the following ----- (20 Marks)

(a) Derivative based Optimization method of steepest descent.

(b) Learning Vector Quantization

(c) ANFIS Application – Printed Character Recognition

(d) Kohonen’s Self Organizing Network.