EECE 565 - Signal Estimation and Detection

This course introduces the fundamental principles underlying the development and analysis of signal estimation and detection, which involve processing information-bearing signals to make inferences about the information that they contain. The course will apply this framework to problems in communications, radar, control, signal processing, and related areas. Topics include minimum variance unbiased estimators, the Cramer-Rao lower bound, maximum likelihood estimation, Bayesian estimation, dynamic parameter estimation and Kalman filtering, advanced hypothesis testing, generalized likelihood ratio testing.

Prerequisites & Notes: EECE 501; EECE 502; or instructor permission.
Credits: 4
Grade Mode: Letter