 MORE IN Neural Networks and Fuzzy Systems
MU Electronics Engineering (Semester 8)
Neural Networks and Fuzzy Systems
December 2013
Total marks: --
Total time: --
INSTRUCTIONS
(1) Assume appropriate data and state your reasons
(2) Marks are given to the right of every question
(3) Draw neat diagrams wherever necessary

1 (a) Compare RBFN and MLP network.
5 M
1 (b) State application of Kohenen self organising maps.
5 M
1 (c) Explain Intersections and Union of fuzzy set
5 M
1 (d) What are various characteristics of ANN
5 M

2 (a) What is learning process ? What do you mean by supervised and unsupervised learning with suitable example
10 M
2 (b) Explain RBF to solve XOR problem
10 M

3 (a) Write an algorithm for back propagation and explain about the updation of weight process
10 M
3 (b) Draw the architecture of Hopfield network. Explain how it is more stable than the BPN.
10 M

4 (a) Explain the following term :
(i) ANFIS
(ii) Brain state in box mode
10 M
4 (b) Explain perceptron convergence theorem
10 M

5 (a) Explain steepest descent algorithm
10 M
5 (b) Explain fuzzy membership functions
10 M

6 (a) Distinguish between self organized learning Networks and Kohenen network
10 M
6 (b) If A is the fizzy set defined by
$A=\frac{0.5}{x_{1}}+\frac{0.4}{x_{0}}+\frac{0.7}{x_{3}}+\frac{0.8}{x_{4}}+\frac{1}{x_{5}}$
List all α cuts of A.
10 M

Write short notes on (any four).
7 (a) Fuzzy controller
5 M
7 (b) Learning factors
5 M
7 (c) Boltzman machine
5 M
7 (d) Neurodynamic model
5 M
7 (e) LMS algorithm
5 M
7 (f) Fuzzy relation and functions.
5 M

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