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research article
Adaptive tracking of linear time-variant systems by extended RLS algorithms
We exploit the one-to-one correspondences between the recursive least-squares (RLS) and Kalman variables to formulate extended forms of the RLS algorithm. Two particular forms of the extended RLS algorithm are considered: one pertaining to a system identification problem and the other pertaining to the tracking of a chirped sinusoid in additive noise. For both of these applications, experiments are presented that demonstrate the tracking superiority of the extended RLS algorithms compared with the standard RLS and least-mean-squares (LMS) algorithms.
Type
research article
Authors
Publication date
1997
Published in
Volume
45
Issue
5
Start page
1118
End page
1128
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
December 19, 2017
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