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Fast Taylor polynomial evaluation for the computation of the matrix cosine

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Fast Taylor polynomial evaluation for the computation of the matrix cosine

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dc.contributor.author Sastre, Jorge es_ES
dc.contributor.author Ibáñez González, Jacinto Javier es_ES
dc.contributor.author Alonso-Jordá, Pedro es_ES
dc.contributor.author Peinado Pinilla, Jesús es_ES
dc.contributor.author Defez Candel, Emilio es_ES
dc.date.accessioned 2020-06-06T03:32:08Z
dc.date.available 2020-06-06T03:32:08Z
dc.date.issued 2019-07 es_ES
dc.identifier.issn 0377-0427 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145535
dc.description.abstract [EN] In this work we introduce a new method to compute the matrix cosine. It is based on recent new matrix polynomial evaluation methods for the Taylor approximation and a mixed forward and backward error analysis. The matrix polynomial evaluation methods allow to evaluate the Taylor polynomial approximation of the matrix cosine function more efficiently than using Paterson-Stockmeyer method. A sequential Matlab implementation of the new algorithm is provided, giving better efficiency and accuracy than state-of-the-art algorithms. Moreover, we provide an implementation in Matlab that can use NVIDIA CPUs easily and efficiently. (C) 2018 Elsevier B.V. All rights reserved. es_ES
dc.description.sponsorship This work has been partially supported by Spanish Ministerio de Economía y Competitividad and European Regional Development Fund (ERDF) grants TIN2014-59294-P, and TIN2017-89314-P. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation FEDER/TIN2014-59294-P es_ES
dc.relation FEDER/TIN2017-89314-P es_ES
dc.relation MINISTERIO DE ECONOMIA Y EMPRESA/TIN2014-59294-P es_ES
dc.relation AEI/TIN2017-89314-P-AR es_ES
dc.relation.ispartof Journal of Computational and Applied Mathematics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Matrix es_ES
dc.subject Matrix trigonometric functions es_ES
dc.subject Matrix cosine es_ES
dc.subject Taylor es_ES
dc.subject Fast matrix polynomial evaluation es_ES
dc.subject GPU computing es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Fast Taylor polynomial evaluation for the computation of the matrix cosine es_ES
dc.type Artículo es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1016/j.cam.2018.12.041 es_ES
dc.rights.accessRights Embargado es_ES
dc.date.embargoEndDate 2021-01-03 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Sastre, J.; Ibáñez González, JJ.; Alonso-Jordá, P.; Peinado Pinilla, J.; Defez Candel, E. (2019). Fast Taylor polynomial evaluation for the computation of the matrix cosine. Journal of Computational and Applied Mathematics. 354:641-650. https://doi.org/10.1016/j.cam.2018.12.041 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 17th International Conference on Computational and Mathematical Methods in Science and Engineering (CMMSE 2017) es_ES
dc.relation.conferencedate Julio 04-08,2017 es_ES
dc.relation.conferenceplace Rota, Spain es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.cam.2018.12.041 es_ES
dc.description.upvformatpinicio 641 es_ES
dc.description.upvformatpfin 650 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 354 es_ES
dc.relation.pasarela S\380833 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.contributor.funder European Regional Development Fund es_ES


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