RLS solution for the adaptive recursive filter

The recursive least square (RLS) algorithm is insensitive to the dispersions of the correlation matrix. Consequently, the usage of the RLS algorithm to update the adaptive recursive filter coefficients are attractive for the system modeling and identification fields. In this paper, an error function...

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Bibliographic Details
Published in1996 National Radio Science Conference pp. 451 - 458
Main Author Soliet, E.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Adaptive control
Adaptive filters
Convergence
Digital signal processors
Iterative algorithms
Least squares methods
Mean square error methods
Modeling
Resonance light scattering
Signal processing algorithms
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ISBN0780336569
9780780336568
DOI10.1109/NRSC.1996.551135

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Summary:The recursive least square (RLS) algorithm is insensitive to the dispersions of the correlation matrix. Consequently, the usage of the RLS algorithm to update the adaptive recursive filter coefficients are attractive for the system modeling and identification fields. In this paper, an error function RLS (EFRLS) algorithm is derived for the adaptive recursive filter. Furthermore, a scaled version of the EFRLS algorithm is proposed where the computation complexity is significantly reduced. The scaled EFRLS algorithm can be realized in real time using the available digital signal processors. The convergence to the optimal solution of both the EFRLS algorithm and its scaled version is ensured while the general RLS algorithm fails to converge to the optimal solution for the multimodal performance criterion.
ISBN:0780336569
9780780336568
DOI:10.1109/NRSC.1996.551135