This download link is referred from the post: JNTUA M.Tech 1st Sem last 10 year 2010-2020 Previous Question Papers (JNTU Anantapur)
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Code: 9D06105
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M.Tech I Semester Regular & Supplementary Examinations January/February 2017
NEURAL NETWORKS & APPLICATIONS
(Common to DSCE & ECE)
Time: 3 hours
Max. Marks: 60
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Answer any FIVE questions
All questions carry equal marks
- (a) Define activation function and discuss about various linear and non-linear activation functions.
(b) What is neural learning? Explain about supervised, unsupervised and reinforcement learning rules. - (a) Briefly discuss about linear separability and the solution for EX-OR problem.
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(b) Discuss the perceptron training algorithm with a suitable example. What are its limitations? Explain. - (a) Explain the process of multi class discrimination.
(b) Discuss in detail the various matters relating to the performance of a multilayer perceptron trained with the back-propagation algorithm. - (a) Give the architecture and explain the training algorithm for radial basis function network. Compare radial basis network with multiplayer perceptron.
(b) Write short note on polynomial networks. - (a) What is learning vector quantizer? Explain.
(b) Describe adaptive resonance theory (ART) with an example. - (a) Describe hamming net and maxnet with an example.
(b) Draw the architecture and explain the training algorithm of full counter propagation networks. - (a) Give the architecture of Hopfield network and explain the training algorithm. Define energy function for auto association and explain how it can be minimized.
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(b) Using Hebb rule of discrete BAM, find the weight matrix to store the following input and output pattern pairs: S₁ = (1, 1, 0) T₁ (1, 0) S₂ = (0, 1, 0) T₂ (0, 1) - (a) Describe how Hopfield network can be used as analog to digital converter.
(b) Explain in brief applications of neural networks in image processing.
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This download link is referred from the post: JNTUA M.Tech 1st Sem last 10 year 2010-2020 Previous Question Papers (JNTU Anantapur)