A guided genetic algorithm for diagonalization of symmetric and Hermitian matrices
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http://hdl.handle.net/10045/84031
Títol: | A guided genetic algorithm for diagonalization of symmetric and Hermitian matrices |
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Autors: | Villacampa, Yolanda | Navarro-González, Francisco J. | Compañ, Patricia | Satorre Cuerda, Rosana |
Grups d'investigació o GITE: | Modelización Matemática de Sistemas | Informática Industrial e Inteligencia Artificial |
Centre, Departament o Servei: | Universidad de Alicante. Departamento de Matemática Aplicada | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial |
Paraules clau: | Eigenvector | Genetic algorithm | Real symmetric matrices | Hermitian matrices |
Àrees de coneixement: | Matemática Aplicada | Ciencia de la Computación e Inteligencia Artificial |
Data de publicació: | de febrer-2019 |
Editor: | Elsevier |
Citació bibliogràfica: | Applied Soft Computing. 2019, 75: 180-189. doi:10.1016/j.asoc.2018.11.004 |
Resum: | The eigenvalues and eigenvectors of a matrix have many applications in engineering and science, such us studying and solving structural problems in both the treatment of signal or image processing, and the study of quantum mechanics. One of the most important aspects of an algorithm is the speed of execution, especially when it is used in large arrays. For this reason, in this paper the authors propose a new methodology using a genetic algorithm to compute all the eigenvectors and eigenvalues in real symmetric and Hermitian matrices. The algorithm uses a general-purpose library developed by the authors for genetic algorithms (GALGA). The speed of execution and the influence of population size have been studied. Moreover, the algorithm has been tested in different matrices and population sizes by comparing the speed of execution to the number of the eigenvectors. This new methodology is faster than the previous algorithm developed by the authors and all eigenvectors can be obtained with it. In addition, the performance using the Coope matrix has been tested contrasting the results with another technique published in the scientific literature. |
URI: | http://hdl.handle.net/10045/84031 |
ISSN: | 1568-4946 (Print) | 1872-9681 (Online) |
DOI: | 10.1016/j.asoc.2018.11.004 |
Idioma: | eng |
Tipus: | info:eu-repo/semantics/article |
Drets: | © 2018 Elsevier B.V. |
Revisió científica: | si |
Versió de l'editor: | https://doi.org/10.1016/j.asoc.2018.11.004 |
Apareix a la col·lecció: | INV - MMS - Artículos de Revistas INV - Smart Learning - Artículos de Revistas INV - i3a - Artículos de Revistas |
Arxius per aquest ítem:
Arxiu | Descripció | Tamany | Format | |
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2019_Villacampa_etal_ApplSoftCompJ_final.pdf | Versión final (acceso restringido) | 1,31 MB | Adobe PDF | Obrir Sol·licitar una còpia |
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