DocumentCode
894757
Title
A QR-type algorithm for fitting the delta AR model to autocorrelation windowed data
Author
Zarowski, Christopher J.
Author_Institution
Dept. of Electr. Eng., Queen´´s Univ., Kingston, Ont., Canada
Volume
41
Issue
4
fYear
1993
fDate
4/1/1993 12:00:00 AM
Firstpage
1728
Lastpage
1730
Abstract
A QR algorithm is developed to fit the delta autoregressive (DAR) model of Vijayan et al. (see IEEE Trans. Automat. Cont. vol.36, p.314, 1991) to autocorrelation windowed sampled data. To obtain the DAR model parameters, one must solve a linear system in the matrix called Q n. Unfortunately, there is presently no way to obtain good estimates of Q n. The proposed QR -type algorithm overcomes this problem by computing the DAR model parameters without the need for estimating Q n directly. The QR algorithm proposed is a simple modification of the classical QR algorithm for the conventional AR model due to C.P. Rialan and L.L. Scharf (1986)
Keywords
correlation theory; matrix algebra; signal processing; QR algorithm; autocorrelation windowed data; delta AR model; linear system; matrix; model parameters; sampled data; Autocorrelation; Filtering; Kalman filters; Linear systems; Riccati equations; Sampling methods; Signal processing algorithms; State feedback;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.212757
Filename
212757
Link To Document