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research article
Robust FxLMS algorithms with improved convergence performance
This paper proposes two modifications of the filtered-x least mean squares (FxLMS) algorithm with improved convergence behavior albeit at the same computational cost of 2M operations per time step as the original FxLMS update. The paper further introduces a generalized FxLMS recursion and establishes that the various algorithms are all of filtered-error form. A choice of the stepsize parameter that guarantees faster convergence and conditions for robustness are also derived. Several simulation results are included to illustrate the discussions.
Type
research article
Authors
Publication date
1998
Publisher
Published in
Volume
6
Issue
1
Start page
78
End page
85
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
December 19, 2017
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