Computing the Matrix Exponential with an Optimized Taylor Polynomial Approximation
Visualitza/
Metadades
Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
comunitat-uji-handle4:
INVESTIGACIONMetadades
Títol
Computing the Matrix Exponential with an Optimized Taylor Polynomial ApproximationData de publicació
2019Editor
MDPIISSN
2227-7390Cita bibliogràfica
BADER, Philipp; BLANES, Sergio; CASAS, Fernando. Computing the Matrix Exponential with an Optimized Taylor Polynomial Approximation. Mathematics, 2019, vol. 7, no 12, p. 1174.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://www.mdpi.com/2227-7390/7/12/1174Versió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
A new way to compute the Taylor polynomial of a matrix exponential is presented
which reduces the number of matrix multiplications in comparison with the de-facto standard
Paterson-Stockmeyer method for polynomial ... [+]
A new way to compute the Taylor polynomial of a matrix exponential is presented
which reduces the number of matrix multiplications in comparison with the de-facto standard
Paterson-Stockmeyer method for polynomial evaluation. Combined with the scaling and squaring
procedure, this reduction is sufficient to make the Taylor method superior in performance to Padé
approximants over a range of values of the matrix norms. An efficient adjustment to make the method
robust against overscaling is also introduced. Numerical experiments show the superior performance
of our method to have a similar accuracy in comparison with state-of-the-art implementations,
and thus, it is especially recommended to be used in conjunction with Lie-group and exponential
integrators where preservation of geometric properties is at issue. [-]
Publicat a
Mathematics 2019, 7, 1174.Proyecto de investigación
MTM2016-77660-P (AEI/FEDER, UE)Drets d'accés
info:eu-repo/semantics/openAccess
Apareix a les col.leccions
- IMAC_Articles [121]
- MAT_Articles [759]
Els següents fitxers sobre la llicència estan associats a aquest element:
Except where otherwise noted, this item's license is described as © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).