dc.creatorDai, YH
dc.creatorMartinez, JM
dc.creatorYuan, JY
dc.date2003
dc.dateJUN
dc.date2014-11-18T20:17:22Z
dc.date2015-11-26T16:58:33Z
dc.date2014-11-18T20:17:22Z
dc.date2015-11-26T16:58:33Z
dc.date.accessioned2018-03-28T23:46:09Z
dc.date.available2018-03-28T23:46:09Z
dc.identifierNumerical Linear Algebra With Applications. John Wiley & Sons Ltd, v. 10, n. 4, n. 323, n. 334, 2003.
dc.identifier1070-5325
dc.identifierWOS:000183463200003
dc.identifier10.1002/nla.305
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/54431
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/54431
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/54431
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1277952
dc.descriptionThe search direction in unconstrained minimization algorithms for large-scale problems is usually computed as an iterate of the preconditioned) conjugate gradient method applied to the minimization of a local quadratic model. In line-search procedures this direction is required to satisfy an angle condition that says that the angle between the negative gradient at the current point and the direction is bounded away from pi/2. In this paper, it is shown that the angle between conjugate gradient iterates and the negative gradient strictly increases as far as the conjugate gradient algorithm proceeds. There is fore, the interruption of the conjugate gradient sub-algorithm when the angle condition does not hold is theoretically justified. Copyright (C) 2002 John Wiley Sons, Ltd.
dc.description10
dc.description4
dc.description323
dc.description334
dc.languageen
dc.publisherJohn Wiley & Sons Ltd
dc.publisherW Sussex
dc.publisherInglaterra
dc.relationNumerical Linear Algebra With Applications
dc.relationNumer. Linear Algebr. Appl.
dc.rightsfechado
dc.rightshttp://olabout.wiley.com/WileyCDA/Section/id-406071.html
dc.sourceWeb of Science
dc.subjectconjugate gradients
dc.subjectunconstrained minimization
dc.subjecttruncated Newton methods
dc.subjecttruncated quasi-Newton methods
dc.subjectlarge scale problems
dc.subjectOptimization
dc.titleAn increasing-angle property of the conjugate gradient method and the implementation of large-scale minimization algorithms with line searches
dc.typeArtículos de revistas


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