dc.creatorScolnik, Hugo Daniel
dc.creatorEchebest, Nélida Ester
dc.creatorGuardarucci, María Teresa
dc.date2009
dc.date2019-10-04T12:28:18Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/82673
dc.identifierissn:1547-5816
dc.descriptionThe aim of this paper is to extend the applicability of an algorithm for solving inconsistent linear systems to the rank-deficient case, by employing incomplete projections onto the set of solutions of the augmented system Ax-r = b. The extended algorithm converges to the unique minimal norm solution of the least squares solutions. For that purpose, incomplete oblique projections are used, defined by means of matrices that penalize the norm of the residuals. The theoretical properties of the new algorithm are analyzed, and numerical experiences are presented comparing its performance with some well-known projection methods.
dc.descriptionFacultad de Ciencias Exactas
dc.descriptionFacultad de Ingeniería
dc.formatapplication/pdf
dc.format175-191
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Exactas
dc.subjectIncomplete oblique projections
dc.subjectMinimal norm solution
dc.subjectRank-deficient least-squares problems
dc.titleExtensions of incomplete oblique projections method for solving rank-deficient least-squares problems
dc.typeArticulo
dc.typeArticulo


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