EEL6825: Syllabus

EEL 6825 - Pattern Recognition - Fall 1999

Instructor: John G. Harris
Office: NEB 453
Phone: (352) 392-2652
Email: harris@cnel.ufl.edu
Homepage: http://www.cnel.ufl.edu/analog/harris.html
Office hours: MTW 8am
US Mailing Address:
Department of Electrical and Computer Engineering
University of Florida
453 NEB, Bldg. 33
PO Box 116130
Gainesville, FL 32611-6130

TA: Jeremy Ward
Office: NEB 288
Phone: N/A
Email: jeremy.ward@isi-web.com
Office hours: 10:30am-noon Thursday and Friday

Prerequisite: The course assumes previous programming experience and some familiarity with linear algebra and statistics (normally obtained through undergraduate coursework).

Class Meeting: MWF 7th period (1:55pm-2:45pm), 330 Larsen

Class Homepage: http://www.cnel.ufl.edu/analog/courses/EEL6825

Required textbook: Sergios Theodoridis and Konstantinos Koutroumbas, Pattern Recognition, Academic Press, 1998 ; ISBN: 0126861404

Reference Books:

• Neural Networks for Pattern Recognition, Christopher M. Bishop, Oxford University Press, 1995.
• Pattern Classification and Scene Analysis by Richard Duda and Peter Hart, John Wiley & Sons 1973.
• Introduction to Statistical Pattern Recognition by Keinosuke Fukunaga, Academic Press 1990.

Course Objectives: This class provides an introduction to classical pattern recognition. Pattern recognition is the assignment of a physical object or event to one of several prescribed categories. This semester will include sections on neural networks and provide links to the classical statistical pattern recognition techniques. Applications include automated speech recognition, fingerprint identification and optical character recognition. Major topics include:

• Bayesian decision theory.
• Parametric estimation and supervised learning.
• Linear discriminant functions.
• Nonparametric methods.
• Feature extraction for representation and classification.
• Neural networks for pattern recognition

Grade Determination:

• 25% Homework
• 25% Exam 1
• 25% Exam 2
• 25% Final Project

Exam Dates:

• Exam 1, Weds, October 6, period E1-E3 (7:20pm-10:10pm), NEB202
• Exam 2, Weds, November 17, period E1-E3 (7:20pm-10:10pm), NEB202