ECE 644 - Estimation and Filtering Theory

3 credit(s)
Bayesian estimation theory; maximum likelihood estimation; linear minimum variance estimation; discrete and continuous Kalman filters; colored noise, smoothing, and prediction; first-order nonlinear Kalman filter; applications to communication and control.
Prerequisite(s): Graduate standing with ECE 521, ECE 642, M 515, and M 517; or equivalent.

Click here for Fall 2024 course scheduling information.

Click here for Spring 2025 course scheduling information.