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

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

Overview

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

Terms: This course is not scheduled for the 2021-2022 academic year.

Instructors: There are no professors associated with this course for the 2021-2022 academic year.

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