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Article Dans Une Revue IEEE Transactions on Signal Processing Année : 2014

A Recursive Restricted Total Least-squares Algorithm

Résumé

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.
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Dates et versions

hal-01067938 , version 1 (24-09-2014)

Identifiants

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Stephan Rhode, Konstantin Usevich, Ivan Markovsky, Frank Gauterin. A Recursive Restricted Total Least-squares Algorithm. IEEE Transactions on Signal Processing, 2014, 62 (21), pp.5652-5662. ⟨10.1109/TSP.2014.2350959⟩. ⟨hal-01067938⟩
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