SPPU Electronics and Telecom Engineering (Semester 8)
Soft Computing Techniques
December 2016
Total marks: --
Total time: --
INSTRUCTIONS
(1) Assume appropriate data and state your reasons
(2) Marks are given to the right of every question
(3) Draw neat diagrams wherever necessary


Solve any one question from Q.1(a,b,c)& Q2.(a,b,c)
1(a) Using Mc-Culloch Pitts neuron, implement a bipolar AND function. Assume initial weights to be[1 1].
8 M
1(b) Explain unsupervised learning mechanism in contrast with a supervised learning mechanism.
6 M
1(c) State the algorithm and essential processes in a Self Organized Feature Map network.
6 M

2(a) State the perceptron learning rule. Also explain its limitation and solution for the same.
8 M
2(b) State and explain the popular topologies of neural networks.
6 M
2(c) Explain the RBF network and state its learning mechanism.
6 M

Solve any one question from Q.3(a,b)& Q.4(a,b)
3(a) Explain any one fuzzy membership function with its transfer characteristics. Describe the possible use of the same with a suitable example.
8 M
3(b) Using max-min composition find relation between R and S.
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8 M

4(a) State the Charactertistics of Neuro-fuzzy and soft computing.
8 M
4(b) Consider two fuzzy sets A and B, calculate \[A\cap \bar{B}\text{and}B\cap {\bar{A}}\]. \(\begin{align*} A=\left \{ \frac{0.1}{2} ,\frac{0.6}{3},\frac{0.4}{4},\frac{0.3}{5},\frac{0.8}{6}\right \}\\ B=\left \{ \frac{0.5}{2},\frac{0.8}{3},\frac{0.4}{4},\frac{0.6}{5},\frac{0.4}{6} \right \}\end{align*} \)/
8 M

Solve any one question from Q.5(a,b)& Q.6(a,b)
5(a) Explain the procedure for designing a simple fuzzy control system.
8 M
5(b) Draw and explain the architecture of a typical FLC.
8 M

6(a) State the fuzzy compositional rules used for fuzzy relationship computation.
8 M
6(b) Give a rule: IF x is A, THEN y is B, where \(A=\left \{ \frac{0.2}{1} ,\frac{0.5}{2},\frac{0.7}{2}\right \}\text{and}B=\left \{ \frac{0.6}{5},\frac{0.8}{7},\frac{0.4}{9} \right \} \)/ inter B' for another rule: IF x is A' THEN y is B', where \( A=\left \{ \frac{0.5}{1} ,\frac{0.9}{2},\frac{0.3}{3}\right \} \)/ using Zadeh implication rule. Implication rule.
8 M

Solve any one question from Q.7(a,b)& Q.8(a,b)
7(a) Draw and explain the architecture of a typical FLC.
10 M
7(b) State the Archiecture of ANFIS.
8 M

8(a) State the various application of FLC.
10 M
8(b) Write a short note on "Hybrid Learning Algorithm employed in ANFIS"
8 M



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