Two algorithms for computing the matrix cosine function

[EN] The computation of matrix trigonometric functions has received remarkable attention in the last decades due to its usefulness in the solution of systems of second order linear differential equations. Several state-of-the-art algorithms have been provided recently for computing these matrix func...

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Detalhes bibliográficos
Autores: Sastre, Jorge|||0000-0002-8612-6717, Ibáñez González, Jacinto Javier|||0000-0002-6912-4453, Alonso-Jordá, Pedro|||0000-0002-6882-6592, Peinado Pinilla, Jesús|||0000-0002-9048-5106, Defez Candel, Emilio|||0000-0002-3303-6371
Formato: artículo
Fecha de publicación:2017
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/99127
Acesso em linha:https://riunet.upv.es/handle/10251/99127
Access Level:acceso abierto
Palavra-chave:Matrix cosine,Scaling and recovering method,Taylor series,Forward error analysis,Backward error analysis,MATLAB
MATEMATICA APLICADA
LENGUAJES Y SISTEMAS INFORMATICOS
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
TEORIA DE LA SEÑAL Y COMUNICACIONES
Descrição
Resumo:[EN] The computation of matrix trigonometric functions has received remarkable attention in the last decades due to its usefulness in the solution of systems of second order linear differential equations. Several state-of-the-art algorithms have been provided recently for computing these matrix functions. In this work, we present two efficient algorithms based on Taylor series with forward and backward error analysis for computing the matrix cosine. A MATLAB implementation of the algorithms is compared to state-of-the-art algorithms, with excellent performance in both accuracy and cost.