DISTANCE EDUCATION
M.C.A./M.C.A. (Lateral) DEGREE EXAMINATION,
MAY 2018.
Sixth Semester
NEURAL NETWORKS
(2005 to 2010 Calendar Year)
Time Three hours Maximum 100 marks
Answer any FIVE questions.
All questions carry equal marks.
x 20 100)
1. Explain briefly about the architecture of neural networks.
Discuss about the benefits of ANN.
2. Explain about the various learning tasks.
Write brief note on competitive learning.
3. Briefly explain the multilayer training algorithms.
What are the limitations of back propagation networks?
4. Explain the relation between perceptron and bayes classifier in gaussian environment.
Explain the various applications of Hop field network.
Sub. Code
63
DE-3867
2
Sp 1
5. Define perceptrons. Explain its various algorithms.(10)
Discuss in detail about associative memory.
6. Explain briefly about the energy function for bidirectional associative memory.
Discuss in detail about least mean-square algorithm.
7. Compare cognitron and neocognitron.
Discuss briefly about the overview of adaptive resonance theory.
8. Explain briefly about the holographic correlators.
Describe in detail about the structure of optical neural network.