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dc.contributor.authorAl Khoury, Philippe
dc.contributor.authorChavent, Guy
dc.date.accessioned2014-06-24T15:42:11Z
dc.date.available2014-06-24T15:42:11Z
dc.date.issued2006
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/13588
dc.descriptionSpecial Issue: Proceedings of the Inverse Problems, Design and Optimization (IPDO-2004) Symposium, Rio de Janeiro, Brazil, March 17–19 2004
dc.language.isoenen
dc.subjectOptimizationen
dc.subjectNonlinear least squaresen
dc.subjectLine searchen
dc.subjectCurvature step\-sizesen
dc.subject.ddc518en
dc.titleGlobal line search strategies for nonlinear least squares problems based on curvature and projected curvatureen
dc.typeCommunication / Conférence
dc.description.abstractenIn this article, we introduce global line search strategies based on the maximum projected curvature step (MPCS). This step is developed from the maximum curvature step (MCS), defined in [Chavent, G., 2004, Curvature steps and geodesic moves for nonlinear least squares descent algorithms. Inverse Problems in Science and Engineering.] and [Chavent, G., 2002, Curvature steps and geodesic moves for nonlinear least squares descent algorithms, INRIA Report.]. At a point in a descent curve, we introduce the optimization plan, on which we project the acceleration in order to obtain the projected curvature. For a search curve with bounded projected curvature, we compute the lower bound to the arc length of the first stationary point, which defines the MPCS. The convergence of the global strategies based on MPCSs and MCSs is studied for different common descent directions. Preliminary numerical results show that algorithms using the new strategies with steepest descent, Gauss–Newton or Levenberg–Marquardt direction are more efficient than the corresponding ones based on the unit step-size.en
dc.relation.isversionofjnlnameInverse Problems in Science and Engineering
dc.relation.isversionofjnlvol14
dc.relation.isversionofjnlissue5
dc.relation.isversionofjnldate2006
dc.relation.isversionofjnlpages495-509
dc.relation.isversionofdoihttp://dx.doi.org/10.1080/17415970600573684
dc.relation.isversionofjnlpublisherTaylor & Francis
dc.subject.ddclabelModèles mathématiques. Algorithmesen
dc.relation.conftitleInverse Problems, Design and Optimization (IPDO-2004) Symposiumen
dc.relation.confdate2006-03
dc.relation.confcityRio de Janeiroen
dc.relation.confcountryBrésilen
dc.relation.forthcomingnonen


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