E C E 830: Estimation and Decision Theory
- Catalog Description:
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.
- Credits: 3
- Prerequisites: ECE 730 or equiv
- Official Course Description (pdf)