DocumentCode
1352462
Title
Gauss Newton variable forgetting factor recursive least squares for time varying parameter tracking
Author
Song, Seongwook ; Lim, Jun-Seok ; Baek, Seongjoon ; Sung, Koeng-Mo
Author_Institution
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
Volume
36
Issue
11
fYear
2000
fDate
5/25/2000 12:00:00 AM
Firstpage
988
Lastpage
990
Abstract
The Gauss-Newton variable forgetting factor recursive least squares (GN-VFF-RLS) algorithm is presented, which can be used to improve the tracking capability in time varying parameter estimation. Compared to the existing algorithm, the exponentially windowed recursive least squares (EW-RLS) algorithm with optimal forgetting factor, the presented method leads to a significant improvement in fast time varying parameter estimation. The effects of signal to noise ratio and nonstationarity have been tested using computer simulations with the given parameter model. An assessment of the performance of each algorithm is presented in terms of the mean-square-deviation (MSD).
Keywords
time-varying systems; Gauss Newton variable forgetting factor RLS algorithm; SNR effects; mean-square-deviation; nonstationarity effects; recursive least squares algorithm; signal to noise ratio; time varying parameter estimation; time varying parameter tracking;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:20000727
Filename
849013
Link To Document