Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 18, Issue 3, Pages 185-188Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2011.2106119
Keywords
Adaptive filters; RLS adaptation algorithms; robust adaptation algorithms
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Funding
- Natural Sciences and Engineering Research Council of Canada
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A new robust recursive least-squares (RLS) adaptive filtering algorithm that uses a priori error-dependent weights is proposed. Robustness against impulsive noise is achieved by choosing the weights on the basis of the norms of the crosscorrelation vector and the input-signal autocorrelation matrix. The proposed algorithm also uses a variable forgetting factor that leads to fast tracking. Simulation results show that the proposed algorithm offers improved robustness as well as better tracking compared to the conventional RLS and recursive least-M estimate adaptation algorithms.
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