Fast Taylor polynomial evaluation for the computation of the matrix cosine
[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 appr...
| Autores: | , , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2019 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglês |
| OAI Identifier: | oai:riunet.upv.es:10251/145535 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/145535 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Matrix Matrix trigonometric functions Matrix cosine Taylor Fast matrix polynomial evaluation GPU computing TEORIA DE LA SEÑAL Y COMUNICACIONES CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL MATEMATICA APLICADA |
| Resumo: | [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. |
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