EE5251
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EE 5251 - Optimal Filtering and Estimation (3 Cr.) Online may be available
Electrical and Computer Engineering (11122)
TIOT - College of Science and Engineering
Course description
Basic probability theory, stochastic processes. Gauss-Markov model. Batch/recursive least squares estimation. Filtering of linear/nonlinear systems. Continuous-time Kalman-Bucy filter. Unscented Kalman filter, particle filters. Applications.
prereq: [[[MATH 2243, STAT 3021] or equiv], CSE grad student] or dept consent; 3025, 4231 recommended
prereq: [[[MATH 2243, STAT 3021] or equiv], CSE grad student] or dept consent; 3025, 4231 recommended
Minimum credits
3
Maximum credits
3
Is this course repeatable?
No
Grading basis
OPT - Student Option
Lecture
Requirements
000356
Credit will not be granted if credit has been received for:
01703
Fulfills the writing intensive requirement?
No
Typically offered term(s)
Every Fall