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Linearly-Constrained Recursive Total Least-Squares Algorithm | IEEE Journals & Magazine | IEEE Xplore

Linearly-Constrained Recursive Total Least-Squares Algorithm

Publisher: IEEE

Abstract:

We develop a new linearly-constrained recursive total least squares adaptive filtering algorithm by incorporating the linear constraints into the underlying total least s...View more

Abstract:

We develop a new linearly-constrained recursive total least squares adaptive filtering algorithm by incorporating the linear constraints into the underlying total least squares problem using an approach similar to the method of weighting and searching for the solution (filter weights) along the input vector. The proposed algorithm outperforms the previously proposed constrained recursive least square (CRLS) algorithm when both input and output data are observed with noise. It also has a significantly smaller computational complexity than CRLS. Simulations demonstrate the efficacy of the proposed algorithm.
Published in: IEEE Signal Processing Letters ( Volume: 19, Issue: 12, December 2012)
Page(s): 821 - 824
Date of Publication: 02 October 2012

ISSN Information:

Publisher: IEEE

References

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