Theory and Applications of Pattern Recognition (M E 532) Syllabus
Course Learning Outcomes
Course Learning Outcome
Understand the theory and methods for learning from data, with an emphasis on pattern classification.
Theory and Applications of Pattern Recognition
M E 532
( 3 Credits )
Pattern recognition systems and components; decision theories and classification; discriminant functions; supervised and unsupervised training; clustering; feature extraction and dimensional reduction; sequential and hierarchical classification; applications of training, feature extraction, and decision rules to engineering problems.
ECE 331 or Math 431 or cons inst
Department: MECHANICAL ENGINEERING College: College of Engineering