DocumentCode
1180277
Title
Tracking improvements in fast RLS algorithms using a variable forgetting factor
Author
Toplis, Blake ; Pasupathy, Subbarayan
Author_Institution
Bell-Northern Res., Montreal, Que., Canada
Volume
36
Issue
2
fYear
1988
fDate
2/1/1988 12:00:00 AM
Firstpage
206
Lastpage
227
Abstract
The concept of a variable forgetting factor (VFF) is incorporated into fast recursive least-squares (FRLS) algorithms. Compromises in the data matrix that are needed to do this are examined. Both prewindowed and growing memory covariance algorithms are presented in transversal and lattice structures. Forgetting-factor adaptation schemes, which improve tracking performance over conventional FRLS algorithms, are suggested. Finally, the bias introduced by the use of the VFF is analyzed
Keywords
filtering and prediction theory; least squares approximations; adaptive filtering; covariance algorithms; data matrix; fast RLS algorithms; fast recursive least-squares; lattice structures; tracking performance; transversal structure; variable forgetting factor; Adaptive filters; Arithmetic; Cost function; Covariance matrix; Lattices; Least squares methods; Matched filters; Resonance light scattering; Statistics; Working environment noise;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/29.1514
Filename
1514
Link To Document