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...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | 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 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/99127 |
| Access Level: | acceso abierto |
| Palabra clave: | 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 |
| Sumario: | [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. |
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