Detecting periodicity with horizontal visibility graphs

Núñez, Ángel M.; Lacasa Saiz de Arce, Lucas; Valero Sánchez, Eusebio; Gómez Pérez, Jose Patricio y Luque Serrano, Bartolome (2012). Detecting periodicity with horizontal visibility graphs. "International Journal of Bifurcation And Chaos", v. 22 (n. 7); pp.. ISSN 0218-1274. https://doi.org/10.1142/S021812741250160X.

Descripción

Título: Detecting periodicity with horizontal visibility graphs
Autor/es:
  • Núñez, Ángel M.
  • Lacasa Saiz de Arce, Lucas
  • Valero Sánchez, Eusebio
  • Gómez Pérez, Jose Patricio
  • Luque Serrano, Bartolome
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Bifurcation And Chaos
Fecha: 2012
Volumen: 22
Materias:
Palabras Clave Informales: Horizontal visibility graph; time series; complex networks; periodicity detection; noise filter
Escuela: E.T.S.I. Aeronáuticos (UPM) [antigua denominación]
Departamento: Matemática Aplicada y Estadística [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The horizontal visibility algorithm was recently introduced as a mapping between time series and networks. The challenge lies in characterizing the structure of time series (and the processes that generated those series) using the powerful tools of graph theory. Recent works have shown that the visibility graphs inherit several degrees of correlations from their associated series, and therefore such graph theoretical characterization is in principle possible. However, both the mathematical grounding of this promising theory and its applications are in its infancy. Following this line, here we address the question of detecting hidden periodicity in series polluted with a certain amount of noise. We first put forward some generic properties of horizontal visibility graphs which allow us to define a (graph theoretical) noise reduction filter. Accordingly, we evaluate its performance for the task of calculating the period of noisy periodic signals, and compare our results with standard time domain (autocorrelation) methods. Finally, potentials, limitations and applications are discussed.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
Comunidad de MadridMODELICO (S2009/ESP-1691)Sin especificarSin especificarSin especificar

Más información

ID de Registro: 16712
Identificador DC: http://oa.upm.es/16712/
Identificador OAI: oai:oa.upm.es:16712
Identificador DOI: 10.1142/S021812741250160X
URL Oficial: http://www.worldscientific.com/doi/abs/10.1142/S021812741250160X
Depositado por: Memoria Investigacion
Depositado el: 13 Nov 2014 19:25
Ultima Modificación: 13 Nov 2014 19:25
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