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URN: urn:nbn:de:swb:90-434634
DOI: 10.1109/TSP.2014.2350959

A Recursive Restricted Total Least-squares Algorithm

Rhode, S.; Usevich, K.; Markovsky, I.; Gauterin, F.

We show that the generalized total least squares (GTLS) problem with a singular noise covariance matrix is equivalent to the restricted total least squares (RTLS) problem and propose a recursive method for its numerical solution. The method is based on the generalized inverse iteration. The estimation error covariance matrix and the estimated augmented correction are also characterized and computed recursively. The algorithm is cheap to compute and is suitable for online implementation. Simulation results in least squares (LS), data least squares (DLS), total least squares (TLS), and RTLS noise scenarios show fast convergence of the parameter estimates to their optimal values obtained by corresponding batch algorithms.

Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Zeitschriftenaufsatz
Jahr 2014
Sprache Englisch
Identifikator ISSN: 1053-587X
KITopen ID: 1000043463
Erschienen in IEEE Transactions on Signal Processing
Band 62
Heft 21
Seiten 5652-5662
Bemerkung zur Veröffentlichung This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at,
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