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Detection of mutual phase synchronization in multivariate signals and application to phase ensembles and chaotic data

Please always quote using this URN:urn:nbn:de:0296-matheon-404
  • The work presents a novel method for the detection of mutual phase synchronization in non-stationary time series. We show how the application of a cluster algorithmthat considers spatio-temporal struc- tures of data follows from the general condition of phase-synchronized data. In view of the topology of phasic data, we re-formulate the K-Means cluster algorithm on a flat torus and apply a segmentation index derived in an earlier work (Physica D 177,203-232(2003)). This index is extended by means of averaging in order to reflect phase syn- chronization in ensembles of multivariate time series. The method is illustrated using simulated multivariate phase dynamics and arrays of chaotic systems, in which temporal segments of phase-synchronized states are registered. A comparison with results from an existing bi- variate synchronization index reveals major advantages of our method.

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Metadaten
Author:Axel Hutt, A. Daffershofer, U. Steinmetz
URN:urn:nbn:de:0296-matheon-404
Referee:Anton Bovier
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2004/01/15
Release Date:2004/01/14
Institute:Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS)
Preprint Number:39
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