Detecting periodicity with horizontal visibility graphs

Núñez, Ángel M. and Lacasa Saiz de Arce, Lucas and Valero Sánchez, Eusebio and Gómez Pérez, Jose Patricio and 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.

Description

Title: Detecting periodicity with horizontal visibility graphs
Author/s:
  • Núñez, Ángel M.
  • Lacasa Saiz de Arce, Lucas
  • Valero Sánchez, Eusebio
  • Gómez Pérez, Jose Patricio
  • Luque Serrano, Bartolome
Item Type: Article
Título de Revista/Publicación: International Journal of Bifurcation And Chaos
Date: 2012
ISSN: 0218-1274
Volume: 22
Subjects:
Freetext Keywords: Horizontal visibility graph; time series; complex networks; periodicity detection; noise filter
Faculty: E.T.S.I. Aeronáuticos (UPM)
Department: Matemática Aplicada y Estadística [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

Funding Projects

TypeCodeAcronymLeaderTitle
Madrid Regional GovernmentMODELICO (S2009/ESP-1691)UnspecifiedUnspecifiedUnspecified

More information

Item ID: 16712
DC Identifier: http://oa.upm.es/16712/
OAI Identifier: oai:oa.upm.es:16712
DOI: 10.1142/S021812741250160X
Official URL: http://www.worldscientific.com/doi/abs/10.1142/S021812741250160X
Deposited by: Memoria Investigacion
Deposited on: 13 Nov 2014 19:25
Last Modified: 13 Nov 2014 19:25
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