1 (a)
Explain different types of activation functions

5 M

1 (b)
Explain k.means of algorithm

5 M

1 (c)
Explain any two types of Defuzzification techniques

5 M

1 (d)
How many hidden layers are necessary to approximate a continuous function.

5 M

2 (a)
Write an algorithm for back propagation training and explain about updating of weight

10 M

2 (b)
Explain Hopfield networks in detail.

10 M

3 (a)
Using perceptron learning rule, find the. weights required to perform following classifications. Vector (1 1 1 1) and (-1 1-1-1) are the members of first class.
Vectors (1 1 1-1) and (1 -1 -1 1) are the member of second class. Use two
output neurons. Assume learning rate parameter as 0.9 and initial weight of 0.25. Using training vectors, test the response of net.

10 M

3 (b)
What is meant by simulated annealing. Explain procedure of Boltzman machine with its training phase.

10 M

4 (a)
Explain the method of solving EX-OR problem using RBF and MLP.

10 M

4 (b)
Compare supervised learning with unsupervised learning, Explain with suitable examples.

10 M

5 (a)
Explain the operation of fuzzy logic control with process inference block.

10 M

5 (b)
Write the properties of fuzzy set theory and explain in detail.

10 M

6 (a)
The fuzzy sets are given as follows

\[P=\left \{ \frac{0.1}{2}+\frac{0.3}{4}+\frac{0.7}{6}+\frac{0.4}{8} +\frac{0.2}{10}\right \} \]

\[Q=\left \{ \frac{0.1}{0.1}+\frac{0.3}{0.2}+\frac{0.3}{0.3}+\frac{0.4}{0.4}+\frac{0.5}{0.5}+\frac{0.2}{0.6} \right \}\]

\[R=\left \{ \frac{0.1}{0}+\frac{0.7}{0.5}+\frac{0.3}{1} \right \\]}

Perform the following operations over the fuzzy sets

(i) Max-min composition

(ii) 7 Max product

(iii) Two corss product

\[P=\left \{ \frac{0.1}{2}+\frac{0.3}{4}+\frac{0.7}{6}+\frac{0.4}{8} +\frac{0.2}{10}\right \} \]

\[Q=\left \{ \frac{0.1}{0.1}+\frac{0.3}{0.2}+\frac{0.3}{0.3}+\frac{0.4}{0.4}+\frac{0.5}{0.5}+\frac{0.2}{0.6} \right \}\]

\[R=\left \{ \frac{0.1}{0}+\frac{0.7}{0.5}+\frac{0.3}{1} \right \\]}

Perform the following operations over the fuzzy sets

(i) Max-min composition

(ii) 7 Max product

(iii) Two corss product

10 M

6 (b)
Explain Kohonen's self organizing learning algorithm.

10 M

Write a short note on: (any four)

7 (a)
Brain state-in-a-box model

5 M

7 (b)
Fuzzification Methods

5 M

7 (c)
LMS algorithm

5 M

7 (d)
Neurodynamic Model

5 M

7 (e)
Steepest descent algorithm.

5 M

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