All Courses
EE638 Postgraduate

Estimation and Identification

Credits
6
Type
Theory
Lecture
6 hr
Half sem
No

Course Content

Introduction to linear least square estimation : a geometric approach. Wiener filter, Levinson filter, updating QR filter and the Kalman filter. Filter implementation structures : Lattice, ladder and the systolic QR. Stochastic realization theory (modelling given the covariance). Modelling given the raw data. Spectral estimation. Recursive least squares identification algorithms : Levinson-type, Kalman-type and the QR-type.

Text / References

  1. 1 U.B. Desai, Lecture notes on estimation realization and identification, Unpublished, 1986. B.D.O. Anderson and J.B. Moore, Optimal filtering, Prentice-Hall, 1979. T. Kailath, Lecture notes on Wiener and Kalman filtering, Springer Verlag, 1980. L. Ljung, System identification theory for the user, Prentice-Hall, 1987. P.S. Maybeck, Stochastic models, estimation and control, Vols.1-3, Academic Press, 1980-1982.