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Electrical Engineering
Description: Survey of techniques for identifying patterns present in noisy signal and image data. Includes classifiers, discriminant functions, Bayesian decision theory, maximum likelihood, K-means, relaxation, neural networks, and machine learning. Recommended: A previous course in the fundamentals of signals and systems, including continuous-time and discrete-time signals. Co-convened with EE 443. Letter grade only.
Units: 3
Sections offered: Fall 2026
Prerequisite: Admission to Electrical and Computer Engineering MS
Electrical Engineering
Term : Fall 2026
Catalog Year : 2026-2027
EE 543 - Pattern Recognition
Description: Survey of techniques for identifying patterns present in noisy signal and image data. Includes classifiers, discriminant functions, Bayesian decision theory, maximum likelihood, K-means, relaxation, neural networks, and machine learning. Recommended: A previous course in the fundamentals of signals and systems, including continuous-time and discrete-time signals. Co-convened with EE 443. Letter grade only.
Units: 3
Sections offered: Fall 2026
Prerequisite: Admission to Electrical and Computer Engineering MS