EE 67033 - Applied State Estimation

Institution:

University of Notre Dame

Subject:

Electrical Engineering

Description:

This course covers techniques used in estimating the state of a dynamical system. The course reviews basic concepts in linear systems, Bayesian estimation, and minimum mean-square estimation followed by the introduction of the conventional Kalman filter in both discrete-time and continuous-time formats. The course examines extensions of the Kalman filter that include the extended and unscented Kalman filter as well as the H-infinity filter. The course may also cover some advanced topics in Multi-target tracking, state estimation over networks, and the use of Markov Chain Monte Carlo (MCMC) methods.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.nd.edu

Phone Number:

(574) 631-5000

Regional Accreditation:

North Central Association of Colleges and Schools

Calendar System:

Semester

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