Solving engineering models using hyperbolic matrix functions
In this paper a method for computing hyperbolic matrix functions based on Hermite matrix polynomial expansions is outlined. Hermite series truncation together with Paterson-Stockmeyer method allow to compute the hyperbolic matrix cosine efficiently. A theoretical estimate for the optimal value of it...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2016 |
| 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:10251/84125 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/84125 |
| Access Level: | acceso abierto |
| Palabra clave: | Hermite matrix polynomial Hyperbolic matrix functions Series expansion CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL MATEMATICA APLICADA LENGUAJES Y SISTEMAS INFORMATICOS TEORIA DE LA SEÑAL Y COMUNICACIONES |
| Sumario: | In this paper a method for computing hyperbolic matrix functions based on Hermite matrix polynomial expansions is outlined. Hermite series truncation together with Paterson-Stockmeyer method allow to compute the hyperbolic matrix cosine efficiently. A theoretical estimate for the optimal value of its parameters is obtained. An efficient and highly-accurate Hermite algorithm and a MATLAB implementation have been developed. The MATLAB implementation has been compared with the MATLAB function funm on matrices of different dimensions, obtaining lower execution time and higher accuracy in most cases. To do this we used an NVIDIA Tesla K20 GPGPU card, the CUDA environment and MATLAB. With this implementation we get much better performance for large scale problems. (C) 2015 Elsevier Inc. All rights reserved. |
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