AOE-5784: Model-Based Estimation and Kalman Filtering
Description: Modeling of estimation problems including batch and dynamic problems; stochastic linear and nonlinear dynamic system models including Markov process models; batch nonlinear least-squares estimation; linear Kalman filtering and smoothing algorithms for dynamic problems; square-root information filtering and smoothing; nonlinear Kalman filtering, including the extended Kalman filter, the unscented Kalman filter, and particle filters; covariance analysis; filtering applications.
Pathways: N/A
Course Hours: 4 credits
Corequisites: AOE-5744 or AOE-5754 or ECE-5744 or ME-5544 or ECE-5754 or ME-5554.
Crosslist: N/A
Repeatability: N/A
Sections Taught: 3
Average GPA: 3.57 (rounds to A-)
Strict A Rate (No A-) : 40.90%
Average Withdrawal Rate: 0.00%
| Mark L Psiaki | 2024 | 73.9% | 16.3% | 9.8% | 0.0% | 0.0% | 0.0% | 3.57 | 3 |