Ordinal synchronization: Using ordinal patterns to capture interdependencies between time series.
Date
2018-12-19Author
Estado
info:eu-repo/semantics/publishedVersionMetadata
Show full item recordAbstract
-- We introduce Ordinal Synchronization (OS) as a new measure to quantify synchronization between dy-
namical systems. OS is calculated from the extraction of the ordinal patterns related to two time series,
their transformation into D-dimensional ordinal vectors and the adequate quantification of their align-
ment. OS provides a fast and robust-to noise tool to assess synchronization without any implicit assump-
tion about the distribution of data sets nor their dynamical properties, capturing in-phase and anti-phase
synchronization. Furthermore, varying the length of the ordinal vectors required to compute OS it is pos-
sible to detect synchronization at different time scales. We test the performance of OS with data sets
coming from unidirectionally coupled electronic Lorenz oscillators and brain imaging datasets obtained
from magnetoencephalographic recordings, comparing the performance of OS with other classical metrics
that quantify synchronization between dynamical systems
Ordinal synchronization: Using ordinal patterns to capture interdependencies between time series.
Tipo de Actividad
Artículos en revistasISSN
0960-0779Palabras Clave
--Synchronization Ordinal patterns In-phase synchronization Anti-phase synchronization Nonlinear electronic circuits Brain imaging data sets