F 06000CS361122002 Pages: 3

Reg No.: Name:
APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY
Fifth Semester B.Tech Degree (S,FE) Examination January 2022 (2015 Scheme)

Course Code: CS361
Course Name: SOFT COMPUTING

Max. Marks: 100 Duration: 3 Hours
PARTA
Answer all questions, each carries 3 marks. Marks
1 Explain any three basic connection architectures of neural networks. (3)
2 Calculate the net input to the neuron Y for the network shown in figure. (3)
Compute output of the neuron Y using binary sigmoidal activation function.
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3 Write perceptron training rule. Explain the terms involved in it. (3)
4 Explain any three learning factors of back propagation network. (3)
PART B
Answer any two full questions, each carries 9 marks.
5 2) Design a McCulloch—Pitts neuron to implement AND function. Use binary (6)
data.
0) Explain the training algorithm of Hebb network. (3)
6 ஐ Whatare the different types of learning methods employed in neural networks? (4)
b) How is error propagated in backpropagation network? Explain the phase 11 of (5)
BPN training algorithm.
7 838) Explain the architecture of Adaline network. (3)
b) Implement OR function using Adaline network. Use bipolar inputs. Perform (6)
one epoch of training.
PART ட
Answer all questions, each carries 3 marks.
8 Explain the concept of set membership in fuzzy logic. Illustrate using (൫)

example.

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