On the incomplete oblique projections method for solving box constrained least squares problems
The aim of this paper is to extend the applicability of the incomplete oblique projections method (IOP) previously introduced by the authors for solving inconsistent linear systems to the box constrained case. The new algorithm employs incomplete projections onto the set of solutions of the augmente...
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Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_10171398_v_n_p1_Scolnik |
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todo:paper_10171398_v_n_p1_Scolnik2023-10-03T15:56:23Z On the incomplete oblique projections method for solving box constrained least squares problems Scolnik, H. Echebest, N. Guardarucci, M.T. Box constrained Incomplete projections Inconsistent systems The aim of this paper is to extend the applicability of the incomplete oblique projections method (IOP) previously introduced by the authors for solving inconsistent linear systems to the box constrained case. The new algorithm employs incomplete projections onto the set of solutions of the augmented system Ax - r = b, together with the box constraints, based on a scheme similar to the one of IOP, adding the conditions for accepting an approximate solution in the box. The theoretical properties of the new algorithm are analyzed, and numerical experiences are presented comparing its performance with some well-known methods. © 2013 Springer Science+Business Media New York. INPR English info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_10171398_v_n_p1_Scolnik |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
language |
English |
orig_language_str_mv |
English |
topic |
Box constrained Incomplete projections Inconsistent systems |
spellingShingle |
Box constrained Incomplete projections Inconsistent systems Scolnik, H. Echebest, N. Guardarucci, M.T. On the incomplete oblique projections method for solving box constrained least squares problems |
topic_facet |
Box constrained Incomplete projections Inconsistent systems |
description |
The aim of this paper is to extend the applicability of the incomplete oblique projections method (IOP) previously introduced by the authors for solving inconsistent linear systems to the box constrained case. The new algorithm employs incomplete projections onto the set of solutions of the augmented system Ax - r = b, together with the box constraints, based on a scheme similar to the one of IOP, adding the conditions for accepting an approximate solution in the box. The theoretical properties of the new algorithm are analyzed, and numerical experiences are presented comparing its performance with some well-known methods. © 2013 Springer Science+Business Media New York. |
format |
INPR |
author |
Scolnik, H. Echebest, N. Guardarucci, M.T. |
author_facet |
Scolnik, H. Echebest, N. Guardarucci, M.T. |
author_sort |
Scolnik, H. |
title |
On the incomplete oblique projections method for solving box constrained least squares problems |
title_short |
On the incomplete oblique projections method for solving box constrained least squares problems |
title_full |
On the incomplete oblique projections method for solving box constrained least squares problems |
title_fullStr |
On the incomplete oblique projections method for solving box constrained least squares problems |
title_full_unstemmed |
On the incomplete oblique projections method for solving box constrained least squares problems |
title_sort |
on the incomplete oblique projections method for solving box constrained least squares problems |
url |
http://hdl.handle.net/20.500.12110/paper_10171398_v_n_p1_Scolnik |
work_keys_str_mv |
AT scolnikh ontheincompleteobliqueprojectionsmethodforsolvingboxconstrainedleastsquaresproblems AT echebestn ontheincompleteobliqueprojectionsmethodforsolvingboxconstrainedleastsquaresproblems AT guardaruccimt ontheincompleteobliqueprojectionsmethodforsolvingboxconstrainedleastsquaresproblems |
_version_ |
1782024789666299904 |