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Pattern Recognition and Application

IIT Kharagpur, , Prof. P.K. Biswas

Updated On 02 Feb, 19

Overview

The course has been designed to be offered as an elective to final year under graduate students mainly from Electrical Sciences background. The course syllabus assumes basic knowledge of Signal Processing, Probability Theory and Graph Theory. The course will also be of interest to researchers working in the areas of Machine Vision, Speech Recognition, Speaker Identification, Process Identification etc.

Includes

Lecture 5: Bayes Decision Theory

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

Course Details

COURSE LAYOUT

Week 1 : Introduction
              
Feature Extraction - I
              
Feature Extraction - II

Week 2
Bayes Decision Theory - I
               Bayes Decision Theory - II

Week 3 :  
Normal Density and Discriminant Function - I
                Normal Density and Discriminant Function - II
                
Bayes Decision Theory - Binary Features

Week 4 : 
Maximum Likelihood Estimation
               Probability Density Estimation - I

Week 5 : 
Probability Density Estimation - II
                Probability Density Estimation - III
                Probability Density Estimation  - IV

Week 6 : Dimensionality Problem
                Multiple Discriminant Analysis

Week 7 : Principal Component Analysis - Tutorial
                Multiple Discriminant Analysis - Tutorial
                Perceptron Criteria  - I

Week 8 : Perceptron Criteria  - II
               MSE Criteria
 
Week 9 : Linear Discriminator Tutorial
                Neural Network - I
                Neural Network - II
 
Week 10 : Neural Network -III/ Hopefield Network
                  RBF Neural Network - I
                  
 Week 11 : RBF Neural Network - II
                  Support Vector Machine
                  Clustering -I
 
Week 12 : Clustering -II
                 Clustering -III


                
                

           


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Comments
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Sam

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

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Dembe

Great course. Thank you very much.

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