x
Menu

Pattern Recognition and Application

IIT Kharagpur, , Prof. P.K. Biswas

Updated On 02 Feb, 19

Overview

Introduction:Feature extraction and Pattern Representation - Concept of Supervised and Unsupervised Classification - Introduction to Application Areas;Statistical Pattern Recognition:Bayes Decision Theory - Minimum Error and Minimum Risk Classifiers - Discriminant Function and Decision Boundary - Normal Density - Discriminant Function for Discrete Features - Parameter Estimation;Dimensionality Problem:Dimension and accuracy - Computational Complexity - Dimensionality Reduction - Fisher Linear Discriminant - Multiple Discriminant Analysis;Nonparametric Pattern Classification:Density Estimation - Nearest Neighbour Rule - Fuzzy Classification;Linear Discriminant Functions:Separability - Two Category and Multi Category Classification - Linear Discriminators - Perceptron Criterion - Relaxation Procedure - Minimum Square Error Criterion - Widrow-Hoff Procedure - Ho-Kashyap Procedure - Keslers Construction;Neural Network Classifier:Single and Multilayer Perceptron - Back Propagation Learning - Hopfield Network - Fuzzy Neural Network;Time Varying Pattern Recognition:First Order Hidden Markov Model - Evaluation - Decoding - Learning;Unsupervised Classification:Clustering - Hierarchical Clustering - Graph Based Method - Sum of Squared Error Technique - Iterative Optimization

Includes

Lecture 16: Dimensionality Problem

4.1 ( 11 )


Lecture Details

Pattern Recognition and Application by Prof. P.K. Biswas,Department of Electronics & Communication Engineering,IIT Kharagpur.For more details on NPTEL visit httpnptel.ac.in

Ratings

0


0 Ratings
55%
30%
10%
3%
2%
Comments
comment person image

Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

Reply
comment person image

Dembe

Great course. Thank you very much.

Reply
Send