Exam Details
Subject | neural networks | |
Paper | ||
Exam / Course | m.c.a./ m.c.a.(lateral) | |
Department | ||
Organization | Alagappa University Distance Education | |
Position | ||
Exam Date | May, 2017 | |
City, State | tamil nadu, karaikudi |
Question Paper
DISTANCE EDUCATION
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
MAY 2017.
Sixth Semester
NEURAL NETWORKS
(2005 to 2010 CY)
Time Three hours Maximum 100 marks
Answer any FIVE questions.
All questions carry equal marks.
20 100)
1. What is biological neural network? Explain.
Explain the applications of artificial neural
networks.
2. Define Learning. What are the different types of
learning rules?
Discuss in detail back propagation networks.
3. Differentiate single and multilayer concepts.
Explain counter propagation networks.
4. Illustrate Hopfield network with necessary
diagrams.
Discuss associative memory.
Sub. Code
63
DE-464
2
Sp 2
5. What is Bidirectional Associative Memory
Explain.
Explain adaptive and competitive with necessary
examples.
6. Discuss adaptive resonance theory.
Discuss in detail optical neural network.
7. Explain about holographic correlators.
Differentiate cognition and neo-cognition.
8. Draw the architecture of ART network and explain
in detail.
State the need for training the Neural network.
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
MAY 2017.
Sixth Semester
NEURAL NETWORKS
(2005 to 2010 CY)
Time Three hours Maximum 100 marks
Answer any FIVE questions.
All questions carry equal marks.
20 100)
1. What is biological neural network? Explain.
Explain the applications of artificial neural
networks.
2. Define Learning. What are the different types of
learning rules?
Discuss in detail back propagation networks.
3. Differentiate single and multilayer concepts.
Explain counter propagation networks.
4. Illustrate Hopfield network with necessary
diagrams.
Discuss associative memory.
Sub. Code
63
DE-464
2
Sp 2
5. What is Bidirectional Associative Memory
Explain.
Explain adaptive and competitive with necessary
examples.
6. Discuss adaptive resonance theory.
Discuss in detail optical neural network.
7. Explain about holographic correlators.
Differentiate cognition and neo-cognition.
8. Draw the architecture of ART network and explain
in detail.
State the need for training the Neural network.
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