Estimation and Decision Theory (E C E 830) Syllabus
Course Learning Outcomes
No Course Learning Outcomes for this course.
Estimation and Decision Theory
E C E 830
( 3 Credits )
Estimation and decision theory applied to random processes and signals in noise: Bayesian, maximum likelihood, and least squares estimation; the Kalman filter; maximum likelihood and maximum aposteriori detection; adaptive receivers for channels with unknown parameters or dispersive, fading characteristics; the RAKE receiver; detection systems with learning features.
ECE 730 or equiv
Department: ELECTRICAL AND COMPUTER ENGR College: College of Engineering