Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisite: ECE 5510 and 5530.
Description
Bayesian parameter estimation; unbiased estimators; minimum variance estimators. Sufficient statistics; maximum-likelihood estimation; the Cramer-Rao bound. Linear estimation; minimum-mean-square-error estimation and its geometrical interpretation. Wiener filtering; spectral factorization. Kalman filtering and state-space estimation. Applications of estimation to practical problems including system identification and spectrum estimation.