X hits on this document

209 views

0 shares

0 downloads

0 comments

93 / 93

Page 93 of 93

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY

HYDERABAD

IV Year B.Tech. IT II-SemT P C

4+1*04

PATTERN RECOGNITION

(ELECTIVE - IV)

UNIT - I

Introduction : Machine perception, pattern recognition example, pattern recognition systems, the design cycle, learning and adaptation (Text book-1, p.nos: 1-17).

UNIT - II

Bayesian Decision Theory : Introduction, continuous features – two categories classifications, minimum error-rate classification- zero–one loss function, classifiers, discriminant functions, and decision surfaces (Text book-1, p.nos: 20-27, 29-31).

UNIT-III

Normal density : Univariate and multivariate density, discriminant functions for the normal densitydifferent cases, Bayes decision theory – discrete features, compound Bayesian decision theory and context (Text book-1, p.nos: 31-45,51-54,62-63).

UNIT-IV

Maximum likelihood and Bayesian parameter estimation : Introduction, maximum likelihood estimation, Bayesian estimation, Bayesian parameter estimation–Gaussian case (Text book-1, p.nos: 84-97).

UNIT-V

Un-supervised learning and clustering : Introduction, mixture densities and identifiability, maximum likelihood estimates, application to normal mixtures, K-means clustering. Date description and clustering – similarity measures, criteria function for clustering (Text book-1, p.nos: 517 – 526, 537 – 546).

UNIT-VI

Component analyses : Principal component analysis, non-linear component analysis; Low dimensional representations and multi dimensional scaling (Text book-1, p.nos: 568-570,573 – 576,580-581).

UNIT-VII

Discrete Hidden Morkov Models : Introduction, Discrete–time markov process, extensions to hidden Markov models, three basic problems for HMMs. (Text book -2, p.nos: 321 – 344)

UNIT-VIII

Continuous hidden Markov models : Observation densities, training and testing with continuous HMMs, types of HMMs. (Text book-2, p.nos: 348 – 352)

TEXT BOOKS :

1. Pattern classifications, Richard O. Duda, Peter E. Hart, David G. Stroke. Wiley

    student edition, Second Edition.

2. Fundamentals of speech Recognition, Lawerence Rabiner, Biing – Hwang

   Juang Pearson education.

REFERENCE :

1. Pattern Recognition and Image Analysis – Earl Gose, Richard John baugh, Steve Jost PHI 2004

Document info
Document views209
Page views209
Page last viewedTue Dec 06 16:18:45 UTC 2016
Pages93
Paragraphs3102
Words29541

Comments