CSC 577 - Pattern Recognition

Credits: 3

Prerequisite: CSC 340 or equivalent. This course introduces pattern recognition methods and theory using conventional statistical approaches, neural networks, fuzzy logic, support vectors, and linear principal component analysis (PCA). The course also presents methods for non-linear PCA, clustering, and feature extraction. Students implement algorithms; apply methods to selected problems, and to document findings.

Repeat Policy:
Course may only be taken once for credit

Click here for the class schedule. select Browse Course Catalog or Register for Classes.