(Established under section 3 of UGC Act,1956)
Course & Branch :B.E
Title of the Paper :Fuzzy Logic and Neural Networks
Sub. Code :614PT702(2007
Time : 3 Hours
A (10 x 2 = 20)
Answer ALL the Questions
What are classical sets?
List the properties of crisp sets.
Define core of a membership function.
Define a convex fuzzy set.
List out the differences between artificial neural n
Artificial Neural Network.
What are the classifications of activation function?
What are the different types of learning rules in Neural
(5 x 12 = 60)
Answer ALL the
(a) With a schematic diagram discuss the structural of a
(b) Diagramatically illustrate and discuss McCulloch
Discuss the Back Propagation Training Algorithm with a relevant
iagramatically illustrate and discuss time hop
State the inverted Pendulam problem. Discuss the design of a
neuro controller for the same.
(a) Define the term Fuzzy relation. What is the Cardinality of a
fuzzy relation? Discu
(b) List and discuss the properties of fuzzy relation.
(a) List and Discuss the operations of fuzzy relation.
(b) Tabulate and Discuss the canonical form for a fuzzy rule
(a) Define the term membership fun
ction. Discuss how neural
network can be used in optimization of membership function. (8)
(b) What is a knowledge base? What are its content? Discuss. (4)
Write a short notes on
(a) Genetic Algorithms.
(b) Adaptive fuzzy system.
n the types of Defuzzification method. Explain any one of
Defuzzification method in detail.
Explain with an example application of fuzzy logic controller.