STUPIDSID
1(a)
Define soft computing? Distinguish between soft computing and hard computing.
5 M
1(b)
Explain Mc Culloch Pitts neuron model with the help of an example.
5 M
1(c)
Determine (alfa) α-level sets and strong α-level sets for the following fuzzy set.
A={(1,0.2),
(2.0.5),
(3,0.8),
(4.1),
(5,0.7),
(6,0.3)}
A={(1,0.2),
(2.0.5),
(3,0.8),
(4.1),
(5,0.7),
(6,0.3)}
5 M
1(d)
Explain linear separable and non-linearly separable pattern with example.
5 M
2(a)
What is learning in neural networks? Differentiate between supervised and unsupervised learning.
10 M
2(b)
Explain any four defuzzification methods with suitable example.
10 M
3(a)
Explain error back propagation training algorithm with the help of flowchart.
10 M
3(b)
Explain genetic algorithm with the help of an example.
10 M
4(a)
Prove the following identities:
i) For unipolar continous activation function f '(net) =o(1-o).
ii) For bipolar continuous activation function O = f (net) = \dfrac{2}{1+e^ {λnet} } -1.
i) For unipolar continous activation function f '(net) =o(1-o).
ii) For bipolar continuous activation function O = f (net) = \dfrac{2}{1+e^ {λnet} } -1.
10 M
5(a)
Explain ANFIS architecture with neat diagram.
10 M
5(b)
Explain perceptron learning with the help of an example
10 M
Write short note on any two of the following
6(a)
Winner take all learning rule.
10 M
6(b)
Learning vector quantization.
10 M
6(c)
Character recognition using neural network.
10 M
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