ESTIMATION AND DECISION THEORY

ECE 830

Course 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.

Prerequisties

ECE 730

Satisfies

COMPSCI/ECE/STAT 861

Credits

Not Reported

Offered

Not Reported

Grade Point Average

3.71

12.55% from Historical

Completion Rate

100%

2.15% from Historical

A Rate

71.43%

105.63% from Historical

Class Size

-55.79% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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