Numerical determination for solving the symmetric eigenvector problem using genetic algorithm
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http://hdl.handle.net/10045/63412
Títol: | Numerical determination for solving the symmetric eigenvector problem using genetic algorithm |
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Autors: | Navarro-González, Francisco J. | Compañ, Patricia | Satorre Cuerda, Rosana | Villacampa, Yolanda |
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 | Eigenvalue | Genetic algorithm | Symmetric matrices | Hermitian matrices | Computational methods |
Àrees de coneixement: | Matemática Aplicada | Ciencia de la Computación e Inteligencia Artificial |
Data de publicació: | d’abril-2016 |
Editor: | Elsevier |
Citació bibliogràfica: | Applied Mathematical Modelling. 2016, 40(7-8): 4935-4947. doi:10.1016/j.apm.2015.12.015 |
Resum: | The eigenvalues and eigenvectors of a matrix have many applications in engineering and science. For example they are important in studying and solving structural problems, in the treatment of signal or image processing, in the study of quantum mechanics and in certain physical problems. It is therefore essential to analyze methodologies to obtain the eigenvectors and eigenvalues of symmetric and Hermitian matrices. In this paper the authors present a methodology for obtaining the eigenvectors and eigenvalues of a symmetric or Hermitian matrix using a genetic algorithm. Unlike other methodologies, the process is centred in searching the eigenvectors and calculating the eigenvalues afterwards. In the search of the eigenvectors a genetic-based algorithm is used. Genetic algorithms are indicated when the search space is extended, unknown or with an intricate geometry. Also, the target vector space can be either real or complex, allowing in this way a wider field of application for the proposed method. The algorithm is tested comparing the results with those obtained by other methods or with the values previously known. So, seven applications are included: a real symmetric matrix corresponding to a vibrating system, a complex Hermitian matrix and an important application of the diagonalization problem (Coope matrix) corresponding to quantum mechanics examples, a physical problem in which data are analysed to reduce the number of variables, a comparison with the power method and the studies of a degenerate and an ill-conditioned matrix. |
URI: | http://hdl.handle.net/10045/63412 |
ISSN: | 0307-904X (Print) | 1872-8480 (Online) |
DOI: | 10.1016/j.apm.2015.12.015 |
Idioma: | eng |
Tipus: | info:eu-repo/semantics/article |
Drets: | © 2015 Elsevier Inc. |
Revisió científica: | si |
Versió de l'editor: | http://dx.doi.org/10.1016/j.apm.2015.12.015 |
Apareix a la col·lecció: | INV - MMS - Artículos de Revistas INV - i3a - Artículos de Revistas INV - Smart Learning - Artículos de Revistas |
Arxius per aquest ítem:
Arxiu | Descripció | Tamany | Format | |
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2016_Navarro_etal_ApplMathMod_final.pdf | Versión final (acceso restringido) | 1,65 MB | Adobe PDF | Obrir Sol·licitar una còpia |
2016_Navarro_etal_ApplMathMod_accepted.pdf | Accepted Manuscript (acceso abierto) | 1,02 MB | Adobe PDF | Obrir Vista prèvia |
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