STUPIDSID
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
(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.
\[A=\frac{0.5}{x_{1}}+\frac{0.4}{x_{0}}+\frac{0.7}{x_{3}}+\frac{0.8}{x_{4}}+\frac{1}{x_{5}} \]
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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