Geodesic
Large-scale dual regularized total least squares
Electronic transactions on numerical analysis, Tome 42 (2014), pp. 13-40.

Voir la notice de l'article provenant de la source Electronic Library of Mathematics

Summary: The total least squares (TLS) method is a successful approach for linear problems when not only the right-hand side but also the system matrix is contaminated by some noise. For ill-posed TLS problems, regularization is necessary to stabilize the computed solution. In this paper we present a new approach for computing an approximate solution of the dual regularized large-scale total least squares problem. An iterative method is proposed which solves a convergent sequence of projected linear systems and thereby builds up a highly suitable search space. The focus is on an efficient implementation with particular emphasis on the reuse of information.
Classification : 65F15, 65F22, 65F30
Keywords: total least squares, regularization, ill-posedness, generalized eigenproblem 
@article{ETNA_2014__42__a8,
     author = {Lampe, J\"org and Voss, Heinrich},
     title = {Large-scale dual regularized total least squares},
     journal = {Electronic transactions on numerical analysis},
     pages = {13--40},
     publisher = {mathdoc},
     volume = {42},
     year = {2014},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ETNA_2014__42__a8/}
}
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Lampe, Jörg; Voss, Heinrich. Large-scale dual regularized total least squares. Electronic transactions on numerical analysis, Tome 42 (2014), pp. 13-40. http://geodesic.mathdoc.fr/item/ETNA_2014__42__a8/