PHYS 453 - Pattern Recognition

Lecture Hours: 3
Lab Hours: 0
Credit Hours: 3
Terms Offered: Spring, even years

Introduces pattern recognition methods and applications: decision theory, Principal Component Analysis, neural networks, linear and non-linear discriminant functions, supervised and unsupervised learning, feature extraction, Hidden Markov Models, Kalman Filters, and related methods in the area of applied computing. Prerequisite: CS 120.