sathyabama university - IndiaStudyChannel.com

bigskymanAI and Robotics

Oct 24, 2013 (3 years and 5 months ago)

84 views


Register Number













SATHYABAMA UNIVERSITY

(Established under section 3 of UGC Act,1956)


Course & Branch :B.E
-

P
-
EEE

Title of the Paper :Fuzzy Logic and Neural Networks

Max. Marks:80

Sub. Code :614PT702(2007
-
08
-
09)





Time : 3 Hours

Date

:05/05/2012









Session :FN

______________________________________________________________________________________________________________________



PART
-

A (10 x 2 = 20)



Answer ALL the Questions

1.

What are classical sets?


2.

List the properties of crisp sets.


3.

Define core of a membership function.


4.

Define a convex fuzzy set.


5.

Define Defuzzification.


6.

List out the differences between artificial neural n
etwork and

biological network.


7.

Artificial Neural Network.


8.

What are the classifications of activation function?


9.

Define threshold.


10.

What are the different types of learning rules in Neural

Networks?

PART


B



(5 x 12 = 60)

Answer ALL the

Questions


11.

(a) With a schematic diagram discuss the structural of a

biological neuron.

(b) Diagramatically illustrate and discuss McCulloch
-
Pitts
Neuron model.

(or)

12.

Discuss the Back Propagation Training Algorithm with a relevant

Diagram.



13.

D
iagramatically illustrate and discuss time hop
-
field network.

(or)

14.

State the inverted Pendulam problem. Discuss the design of a

neuro controller for the same.


15.

(a) Define the term Fuzzy relation. What is the Cardinality of a

fuzzy relation? Discu
ss.








(4)


(b) List and discuss the properties of fuzzy relation.


(8)

(or)

16.

(a) List and Discuss the operations of fuzzy relation.


(b) Tabulate and Discuss the canonical form for a fuzzy rule

based system.


17.

(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)

(or)

18.

Write a short notes on



(a) Genetic Algorithms.



(b) Adaptive fuzzy system.


19.

Mentio
n the types of Defuzzification method. Explain any one of

Defuzzification method in detail.

(or)

20.

Explain with an example application of fuzzy logic controller.