ECSE 510. Filtering and Prediction for Stochastic Systems.
Credits: 3
Offered by: Electrical & Computer Engr (Faculty of Engineering)
This course is not offered this catalogue year.
Description
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.
- (3-0-6)
- Prerequisites: ECSE 500 and ECSE 509 or equivalent.