Pattern Recognition

CENG 509

Fall 2008

Instructor: Reza Hassanpour

Office: A215

Email: reza@cankaya.edu.tr

Web: http://ari.cankaya.edu.tr/~reza

Books:

· Theodoridis and Koutroumbas, Pattern Recognition, Academic Press Duda, Hart, and Stork, Pattern Classification, John Wiley & Sons

· Schalkoff, PatternvRecognition. Statistical, Structural, and Neural Approaches

Syllabus

• Introduction
• Pattern recognition systems
• Preprocessing
• Feature selection
• Classification
• Statistical Pattern Recognition
• Bayes decision theory
• Discriminant functions
• Probability estimations
• Nearest neighbor classification
• K-nearest neighbor method
• Linear classifiers
• Principal component analysis
• Fisher linear discriminant
• Non-linear classification
• Cover theorem
• Support vector machines
• Neural networks
• Multilayer perceptrons
• Training by back-propagation
• Context dependant classification
• Markov model
• Hidden Markov model

Evaluation

1. Programming assignments %30

2. Term project %30

3. Final exam %40

Announcement: Project presentations will be on January 7, 2009.

Assignment submission list

Lecture notes

Week1

Week2

Week3

Week4

Week5

Week6

Week7

Neural Networks Tutorial (using MATLAB)