EEL6825: Syllabus

EEL 6825 - Pattern Recognition - Fall 2000

$\parbox{3.0in}{ {\bf Instructor:} John G.~Harris \hfill \newline {\b... ...} {mailto:harris@cnel.ufl.edu} \newline {\bf Office hours:} MTW 2pm \newline }$$\parbox{3.0in}{ {\bf TA:} Signe Redfield \hfill \newline {\bf Office... ...(4:05-4:55), Thurs 6th period (12:50pm-1:40) and 7th period (1:55-2:45) \par }$

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

Class Meeting: MWF 6th period (12:50pm-1:40pm), NEB 102

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

Required textbook: Pattern Recognition: Statistical, Structural and Neural Approaches by Robert J. Schalkoff, John Wiley & Sons, 1991.

Reference Books:

• 
  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.
• 
  Neural Networks for Pattern Recognition
  by Christopher M. Bishop, Oxford University Press, 1995.
• 
  Pattern Recognition
  by Sergios Theodoridis and Konstantinos Koutroumbas, Academic Press, 1998.

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, Monday, October 2, period E1-E3 (7:20pm-10:10pm), NEB101
• 
  Exam 2, Monday, November 13, period E1-E3 (7:20pm-10:10pm), NEB202