Download AKTU B-Tech 8th Sem 2016-17 NCS080 Pattern Recognition Question Paper

Download AKTU (Dr. A.P.J. Abdul Kalam Technical University (AKTU), formerly Uttar Pradesh Technical University (UPTU) B-Tech 8th Semester (Eight Semester) 2016-17 NCS080 Pattern Recognition Question Paper

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B.TECH.
THEORY EXAMINATION (SEM?VIII) 2016-17
PATTERN RECOGNITION
Time : 3 Hours Max. Marks : 100
Note : Be precise in your answer. In case Ofnumerical problem assume data wherever not provided.
SECTION ? A
1. Explain the following: 10 X 2 = 20
(a) Differentiate Classification with Clustering.
(b) What do you mean by pattern recognition? Explain.
(c) What is Learning? Discuss Supervised & Un Supervised Learning.
(d) Discuss Reinforcement Learning.
(e) What is Back Propagation Algorithm?
(f) Discuss N ormal Density Function.
(g) Discuss Cluster Validation.
(h) What is Conditional Probability?
(i) Discuss various Pattern Recognition Approaches.
(j) Discuss Agglomerative Clustering.
SECTION ? B
2. Attempt any five parts of the following questions: 5 x 10 = 50
(3) Discuss the Design Process of the Pattern Recognition System with suitable block
diagram.
(b) What is Bay's Theorem? Explain. Also discuss Bay's Classifier using some example in
detail.
(c) What do you mean by Clustering? Explain. Discuss K?means clustering algorithm with
suitable example.
(d) What is a Discriminant Function? In a two class problem, the likelihood ratio is given
as follows: P (XlCl) / P (X|C2). Write the discriminant function in terms of the
likelihood ratio.
(e) What do you mean by Dimension Reduction? Discuss Principal Component Analysis
(PCA) algorithm for dimension reduction.
(f) What do you mean by Fuzzy Decision making? Also discuss the Fuzzy Classification
using suitable example.
(g) Write an algorithm for K?N earest N eighbor Estimation. Explain.
(h) Explain the following and discuss their significance in Pattern Recognition With
suitable example :
(i) Mean and Covariance
(ii) Chi Square Test.
SECTION ? C
Attempt any two parts of the following questions: 2 x 15 = 30
3 What is Baysian Decision Theory? Discuss Two Class Category Classification in detail.
4 What is Hidden Markov Model (HMM)? Explain following in HMM:
(i) Forward Algorithm
(ii). Backward Algorithm. _
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Write a short note on the following:
(i) Parametric vs. Non?Parametric Pattern Recognition methods.
(ii) Parzen Windows
(iii) Bayesian estimation
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