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dc.contributor.otherUCH. Departamento de Matemáticas, Física y Ciencias Tecnológicas-
dc.contributor.otherProducción Científica UCH 2018-
dc.creatorCandela Pomares, Vicente Francisco-
dc.creatorFalcó Montesinos, Antonio-
dc.creatorRomero Sánchez, Pantaleón David-
dc.date2018-
dc.date.accessioned2019-11-20T05:01:29Z-
dc.date.available2019-11-20T05:01:29Z-
dc.date.issued2018-03-20-
dc.identifier.citationCandela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994. DOI: https://doi.org/10.1016/j.cam.2017.03.008-
dc.identifier.issn0377-0427-
dc.identifier.issn1879-1778 (Electrónico)-
dc.identifier.urihttp://hdl.handle.net/10637/10709-
dc.descriptionEste artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.sciencedirect.com/science/article/abs/pii/S0377042717301188-
dc.descriptionEste es el pre-print del siguiente artículo: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994, que se ha publicado de forma definitiva en https://doi.org/10.1016/j.cam.2017.03.008-
dc.descriptionThis is the pre-peer reviewed version of the following article: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994, which has been published in final form at https://doi.org/10.1016/j.cam.2017.03.008-
dc.description.abstractIn this paper, we establish sufficient conditions for the existence of optimal nonlinear approximations to a linear subspace generated by a given weakly-closed (non-convex) cone of a Hilbert space. Most non-linear problems have difficulties to implement good projection-based algorithms due to the fact that the subsets, where we would like to project the functions, do not have the necessary geometric properties to use the classical existence results (such as convexity, for instance). The theoretical results given here overcome some of these difficulties. To see this we apply them to a fractional model for image deconvolution. In particular, we reformulate and prove the convergence of a computational algorithm proposed in a previous paper by some of the authors. Finally, some examples are given.-
dc.formatapplication/pdf-
dc.language.isoes-
dc.language.isoen-
dc.publisherElsevier-
dc.relationEste trabajo ha sido financiado por la Universidad CEU Cardenal Herrera (PRCEU-UCH 30/10 y PRCEU-UCH 15/03), por la Generalitat Valenciana (GVA PRE 2010/066) y por el Ministerio de Ciencia, Innovación y Universidades (MTM 2088-03597).-
dc.relationUCH. Financiación Autonómica.-
dc.relationUCH. Financiación Universidad-
dc.relation.ispartofJournal of Computational and Applied Mathematics, vol. 330 (mar. 2018).-
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es-
dc.subjectProgramación (Matemáticas) - Aplicaciones en Obras de arte.-
dc.subjectProgramming (Mathematics) in Works of art.-
dc.subjectHilbert space.-
dc.subjectArt - Conservation and restoration.-
dc.subjectAlgoritmos computacionales.-
dc.subjectObras de arte - Restauración.-
dc.subjectComputer algorithms.-
dc.subjectHilbert, Espacio de.-
dc.subjectObras de arte - Conservación.-
dc.titleA general framework for a class of non-linear approximations with applications to image restoration-
dc.typeArtículo-
dc.description.versionPreprint-
dc.identifier.doihttps://doi.org/10.1016/j.cam.2017.03.008-
dc.relation.projectIDPRCEU-UCH 30/10-
dc.relation.projectIDPRCEU-UCH 15/03-
dc.relation.projectIDGVA PRE 2010/066-
dc.relation.projectIDMTM 2088-03597-
dc.centroUniversidad Cardenal Herrera-CEU-
Aparece en las colecciones: Dpto. Matemáticas, Física y Ciencias Tecnológicas




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