University of Wisconsin Madison
Estimation and Decision Theory (E C E 830) Syllabus
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Details
Estimation and Decision Theory
E C E 830 ( 3 Credits )
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.
Prerequisite(s)
ECE 730 or equiv
Department: ELECTRICAL AND COMPUTER ENGR
College: College of Engineering
Instructor
Instructor Name
Instructor Campus Address
instructorEmail@emailaddress.edu
Contact Hours
 
Course Coordinator
ROBERT NOWAK
Text book, title, author, and year
 
Supplemental Materials
 
Required / Elective / Selected Elective
 
ABET Program Outcomes Associated with this Course
Program Specific Student Outcomes
 
Brief List of Topics to be Covered
 
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