Memorias de investigación
Artículos en revistas:
Inferring the connectivity of coupled oscillators from time-series statistical similarity analysis
Año:2015
Áreas de investigación
  • Ciencias naturales y ciencias de la salud
Datos
Descripción
A system composed by interacting dynamical elements can be represented by a network, where the nodes represent the elements that constitute the system, and the links account for their interactions, which arise due to a variety of mechanisms, and which are often unknown. A popular method for inferring the system connectivity (i.e., the set of links among pairs of nodes) is by performing a statistical similarity analysis of the time-series collected from the dynamics of the nodes. Here, by considering two systems of coupled oscillators (Kuramoto phase oscillators and Rössler chaotic electronic oscillators) with known and controllable coupling conditions, we aim at testing the performance of this inference method, by using linear and non linear statistical similarity measures. We find that, under adequate conditions, the network links can be perfectly inferred, i.e., no mistakes are made regarding the presence or absence of links. These conditions for perfect inference require: i) an appropriated choice of the observed variable to be analysed, ii) an appropriated interaction strength, and iii) an adequate thresholding of the similarity matrix. For the dynamical units considered here we find that the linear statistical similarity measure performs, in general, better than the non-linear ones
Internacional
Si
JCR del ISI
Si
Título de la revista
Scientific Reports
ISSN
2045-2322
Factor de impacto JCR
5,578
Información de impacto
Volumen
5
DOI
10.1038/srep10829
Número de revista
Desde la página
10829
Hasta la página
10843
Mes
JUNIO
Ranking
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Participantes
  • Autor: Javier Martín Buldú UPM
  • Autor: Cristina Masoller
  • Autor: Ricardo Sevilla-Escoboza
  • Autor: Giulio Tirabassi
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Tecnologías para Ciencias de la Salud
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB