PHYS/COMP/MATH 546 Pattern Recognition (3)
Three hours of lecture in the lab per week.
Prerequisite : Admission to the Computer Science or Mathematics Graduate Program
The course will introduce the fundamentals of statistical pattern recognition with examples from several application areas, and present competing approaches to exploratory data analysis and classifier design. Techniques for analyzing multidimensional data of various types and scales along with algorithms for feature extraction, projection, clustering and classification of data will be explained. Programming exercises using MatLab and PRTools will be used to implement diverse examples and applications of pattern recognition processes.