DocumentCode
3102281
Title
An algorithm for estimating the time varying AR parameters of a nonstationary process
Author
DeFigueiredo, Rui J P ; Pham, Trung T.
Author_Institution
Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA
fYear
1988
fDate
3-5 Aug 1988
Firstpage
60
Lastpage
64
Abstract
A nonstationary scalar random process represented by an autoregressive (AR) model with rapidly time-varying coefficients is considered. Assuming the observation of this AR process is contaminated by additive white Gaussian noise, the authors estimate the coefficients using the Kalman filtering technique and the solution of the Ricatti equation. Computer simulations have shown favorable results that converge to the true solution
Keywords
Kalman filters; random processes; white noise; Kalman filtering; Ricatti equation; additive white Gaussian noise; autoregressive model; computer simulation; nonstationary scalar random process; time-varying coefficients; Additive white noise; Computer simulation; Contracts; Covariance matrix; Filtering; Gaussian noise; Kalman filters; Random processes; Riccati equations; Sampling methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Spectrum Estimation and Modeling, 1988., Fourth Annual ASSP Workshop on
Conference_Location
Minneapolis, MN
Type
conf
DOI
10.1109/SPECT.1988.206163
Filename
206163
Link To Document