VARDHAMAN COLLEGE OF ENGINEERING
(AUTONOMOUS)
B. Tech VI Semester Regular Examinations, May 2018
(Regulations: VCE-R15)
NEURAL NETWORKS AND FUZZY LOGICS
(Electrical and Electronics Engineering)
Date: 24 May, 2018 FN Time: 3 hours Max Marks: 75
Answer ONE question from each Unit
All Questions Carry Equal Marks
Unit I
1. Differentiate between biological and artificial neural networks with respect to processing,
size, learning, fault tolerance and memory.
6M
Explain the classification of ANN based on Network Topology with relevant diagrams.
9M
2. Explain Binary sigmoidal function and Bipolar sigmoidal function with their expressions. 6M
Discuss Supervised, Unsupervised and Reinforcement Learning with suitable examples.
9M
Unit II
3. Discuss the Perceptron convergence theorem. 5M
Explain back propagation algorithm. Mention its application.
10M
4. Explain credit assignment problem. 5M
Using perceptron net, find the weights required to perform the following pattern
classification. Vectors and are members of class (having target
vectors and are not members of class (having target Using the
training vectors as input, test the response of the net using application algorithm. Use a
learning rat 1 and starting weight 0.
10M
Unit III
5. Discuss the following with respect to Discrete BAM Networks:
i. Weight updation for binary and bipolar vectors
ii. Activation function for both layers for binary and bipolar vectors
6M
Design a Hopfield network for 4-bit bipolar pattern. The training patterns are given as
1 1 1 S
1 1 1 2 S
1 1 1 3 S
Find the weight matrix and the energy for the three input samples.
Determine the pattern to which the sample S 1
9M
6. Discuss the energy function and training algorithm of Continuous Hopfield Network. 9M
A hetero associative net is trained by Hebb outer product rule for input row vectors
1 2 3 4 S x x x x to output row vectors 1 2 t t t . Find the weight matrix.
(110 1 1 S t
(1110) 2 2 S t
011) 3 3 S t
(010 4 4 S t
6M
Unit IV
7. With relevant mathematical expressions, explain the operations on fuzzy relations. 6M
What are different types of membership functions used in Fuzzy Logic? Briefly explain
any three of them.
9M
Cont…2
2
8. Write a note on the following terms:
i. Uncertainty
ii. ii) Membership functions
6M
Given two fuzzy sets as follows:

Find the following:
i. B
ii. B
iii. A
iv. B
v. B
vi. B
vii. B
viii. A B
ix. B
9M
Unit V
9. Find the membership values for the given triangle and identify the suitable method for
membership value assignment.
Fig.1
6M
How is fuzzy output functions defuzzified? Discuss three defuzzification methods with
the corresponding expression and diagram.
9M
10. For the given membership function shown in Fig.2, determine the defuzzified output
value by Centroid method.
6M
What are the different methods to assign membership values to fuzzy variables? Discuss
any two methods in detail with suitable example.