ECE 2372 - PATTERN RECOGNITION

Minimum Credits: 3
Maximum Credits: 3
Long Description Emphasis on machine pattern recognition and learning; Bayes decision theory, parameter estimation, Bayesian belief networks, discriminant functions, supervised learning, nonparametric techniques, feature extraction, principal component analysis, hidden Markov models, expectation-maximization, support vector machines, artificial neural networks, unsupervised learning, clustering, and syntactic pattern recognition.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PROG: Swanson School of Engineering

Click here for class schedule information.

Add to Portfolio.

Close Window