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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
Email:

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.

Outline:

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


Textbook:

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.

Optional:

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

 URL: http://research.microsoft.com/~cmbishop/PRML/index.htm

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).

Link: http://ivut.iut.ac.ir/

Prerequisites: 

Probabilty Theory

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

 

Time: 

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

Term: 
Fall 2017
Grade: 
Graduate