Linearly-Constrained Recursive Total Least-Squares Algorithm.
In: IEEE Signal Processing Letters, Jg. 19 (2012-12-01), Heft 12, S. 821-824
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Zugriff:
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. [ABSTRACT FROM PUBLISHER]
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Titel: |
Linearly-Constrained Recursive Total Least-Squares Algorithm.
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Autor/in / Beteiligte Person: | Arablouei, Reza ; Dogancay, Kutluyıl |
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Zeitschrift: | IEEE Signal Processing Letters, Jg. 19 (2012-12-01), Heft 12, S. 821-824 |
Veröffentlichung: | 2012 |
Medientyp: | academicJournal |
ISSN: | 1070-9908 (print) |
DOI: | 10.1109/LSP.2012.2221705 |
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