Estimation and System Identification

3 credits

Fundamentals of state estimation for linear and nonlinear systems. Discrete and continuous systems. Probability and stochastic systems theory. Models with noise. Kalman-Bucy filters, extended Kalman filters, recursive estimation. Numerical issues in filter design and implementation. Course overlaps with: A E 514 and TECE 555. Prerequisite: either A A 547, E E 547, or M E 547. Offered: jointly with A A 549/E E 549.