Pattern recognition and Application

By Prof. Prabir Kumar Biswas   |   IIT Kharagpur
Learners enrolled: 1184
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.
The course covers feature extraction techniques and representation of patterns in feature space. Measure of similarity between two patterns. Statistical, nonparametric and neural network techniques for pattern recognition have been discussed in this course. Techniques for recognition of time varying patterns have also been covered. Numerous examples from machine vision, speech recognition and movement recognition have been discussed as applications. Unsupervised classification or clustering techniques have also been addressed in this course.
Analytical aspects have been adequately stressed so that on completion of the course the students can apply the concepts learnt in real life problems.

INTENDED AUDIENCE: Any Interested Learners
Course Status : Completed
Course Type : Elective
Duration : 12 weeks
Category :
  • Electrical, Electronics and Communications Engineering
Credit Points : 3
Level : Undergraduate/Postgraduate
Start Date : 25 Jul 2022
End Date : 14 Oct 2022
Enrollment Ends : 08 Aug 2022
Exam Date : 29 Oct 2022 IST

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

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



Books and references


Instructor bio

Prof. Prabir Kumar Biswas

IIT Kharagpur
Dr. Prabir Kr. Biswas completed his B.Tech(Hons), M.Tech and Ph.D from the Department of Electronics and Electrical Communication Engineering, IIT Kharagpur, India in the year 1985, 1989 and 1991 respectively. From 1985 to 1987 he was with Bharat Electronics Ltd. Ghaziabad as a deputy engineer. Since 1991 he has been working as a faculty member in the department of Electronics and Electrical Communication Engineering, IIT Kharagpur, where he is currently holding the position of Professor and Head of the Department. Prof. Biswas visited University of Kaiserslautern, Germany under the Alexander von Humboldt Research Fellowship during March 2002 to February 2003. Prof. Biswas has more than a hundred research publications in international and national journals and conferences and has filed seven international patents. His area of interest are image processing, pattern recognition, computer vision, video compression, parallel and distributed processing and computer networks. He is a senior member of IEEE and was the chairman of the IEEE Kharagpur Section, 2008.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 29 October 2022 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.


Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

MHRD logo Swayam logo


Goto google play store