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dc.contributor.authorGarralda Guillén, Ana Isabel 
dc.contributor.authorKunze, H.
dc.contributor.authorLa torre, D.
dc.contributor.authorRuiz Galán, Manuel 
dc.date.accessioned2023-12-20T10:17:26Z
dc.date.available2023-12-20T10:17:26Z
dc.date.issued2020-12
dc.identifier.citationGarralda-Guillem, A.I., Kunze, H., La Torre, D., Ruiz Galán, M. Using the generalized collage theorem for estimating unknown parameters in perturbed mixed variational equations (2020) Communications in Nonlinear Science and Numerical Simulation, 91, art. no. 105433.es_ES
dc.identifier.urihttps://hdl.handle.net/10481/86365
dc.description.abstractIn this paper, we study a mixed variational problem subject to perturbations, where the noise term is modelled by means of a bilinear form that has to be understood to be “small” in some sense. Indeed, we consider a family of such problems and provide a result that guarantees existence and uniqueness of the solution. Moreover, a stability condition for the solutions yields a Generalized Collage Theorem, which extends previous results by the same authors. We introduce the corresponding Galerkin method and study its convergence. We also analyze the associated inverse problem and we show how to solve it by means of the mentioned Generalized Collage Theorem and the use of adequate Schauder bases. Numerical examples show how the method works in a practical context.es_ES
dc.description.sponsorshipProject MTM2016-80676-P (AEI/FEDER, UE)es_ES
dc.description.sponsorshipJunta de Andalucía Grant FQM359es_ES
dc.language.isoenges_ES
dc.publisherElsevier B.V.es_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es_ES
dc.subjectBoundary value problemses_ES
dc.subjectInverse problemses_ES
dc.subjectMixed variational equationses_ES
dc.subjectParameter estimationes_ES
dc.titleUsing the generalized collage theorem for estimating unknown parameters in perturbed mixed variational equationses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.cnsns.2020.105433
dc.type.hasVersionAMes_ES


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