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ECSE 510 Filtering and Prediction for Stochastic Systems (3 credits)

Note: This is the 2016–2017 edition of the eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or click here to jump to the newest eCalendar.

Offered by: Electrical & Computer Engr (Faculty of Engineering)

Overview

Electrical Engineering : Basic notions. Linear state space (SS) systems. Least squares estimation and prediction: conditional expectations; Orthogonal Projection Theorem. Kalman filtering; innovations; Riccati equation. ARMA and SS systems. Stationary processes; Wold decomposition; spectral factorization; Weiner filtering. The Weiner process; linear stochastic differential equations; continuous time filtering. Chapman-Kolmogorov, Fokker-Plank equations. Applications.

Terms: This course is not scheduled for the 2016-2017 academic year.

Instructors: There are no professors associated with this course for the 2016-2017 academic year.

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