For Better Performance Please Use Chrome or Firefox Web Browser

Statistical Pattern Recognition

Statistical Pattern Recognition

Sundays and Tusedays from 13:00 am to 15:00pm

 Room #29

2nd Semester 1395-1395 (Jan. 2017)

Instructor: Dr. Mohammad Reza Ahmadzadeh

Room Location: ECE  Building - 322
Internal Telephone: Ext. 5370
External Telephone: Iran: +98 (0)31  33915370
Fax: Iran: +98 (0)31 33912451

Office Hours:

I will try to be in my office on Saturdays, Mondays and Wednesdays from 8 :00 to 9 :00 am and but I will always do my best to be available for students by appointment or any time that I am free.

Course Description:

This course covers the fundamentals of Pattern Recognition techniques.


1- Introduction

2- Bayesian decision theory

3- Maximum likelihood and Bayesian parameter estimation

4- Nonparametric techniques

5- Linear Discriminant Functions

6- Algorithm-independent machine learning

7- Unsupervised Learning and Clustering


1- Pattern Recognition, 4th Ed., Theodoridis and Koutroumbas

2- Duda, Hart and Stork, Pattern Classification, Second Edition, Wiley, 2001.

The text book has a web site. In particular, you may find the errata list useful.

Slides from the authors of the book.


1- Bishop, Christopher M.  Pattern Recognition and Machine Learning, 2006


2- Andrew R.Webb • Keith D. Copsey, Statistical Pattern Recognition, 3rd Ed., 2011.


Lecture Notes:

Slides modified by Instructor and lecture notes can be obtained via E-Learning LMS (Enrolled students, Password protected).



Probabilty Theory

Grading Policy: 
Midterm Exam ≈ 25%
HW, Comp. Assignments and projects: ≈ 30%
Final exam ≈ 45%



Sundays and Tusedays from 13:00 am to 15:00pm

Fall 2017