DocumentCode
2277250
Title
Pole estimation by the Yule-Walker equation and the total least squares algorithm
Author
Mossberg, Magnus
Author_Institution
Dept. of Electr. Eng., Karlstad Univ.
fYear
2006
fDate
14-16 June 2006
Abstract
The problem of estimating the poles of a linear time-invariant stochastic continuous-time system from evenly sampled data, affected by discrete-time measurement noise, is studied. The proposed solution is to use the Yule-Walker equation and the total least squares algorithm. The Cramer-Rao lower bound for the estimation problem is derived and the properties of the proposed solution and four other methods are illustrated in a numerical study
Keywords
continuous time systems; discrete time systems; identification; linear systems; matrix algebra; poles and zeros; sampled data systems; stochastic systems; Cramer-Rao lower bound; Yule-Walker equation; discrete-time measurement noise; linear time-invariant stochastic continuous-time system; pole estimation; sampled data system; total least squares algorithm; Equations; Least squares approximation; Least squares methods; Noise measurement; Parameter estimation; Process control; Signal processing algorithms; Stochastic resonance; Stochastic systems; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2006
Conference_Location
Minneapolis, MN
Print_ISBN
1-4244-0209-3
Electronic_ISBN
1-4244-0209-3
Type
conf
DOI
10.1109/ACC.2006.1656461
Filename
1656461
Link To Document