Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains.

@article{Allefeld2007DetectingSC,
  title={Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains.},
  author={Carsten Allefeld and Stephan Bialonski},
  journal={Physical review. E, Statistical, nonlinear, and soft matter physics},
  year={2007},
  volume={76 6 Pt 2},
  pages={
          066207
        }
}
  • Carsten Allefeld, Stephan Bialonski
  • Published in
    Physical review. E…
    2007
  • Physics, Mathematics, Medicine
  • Synchronization cluster analysis is an approach to the detection of underlying structures in data sets of multivariate time series, starting from a matrix R of bivariate synchronization indices. A previous method utilized the eigenvectors of R for cluster identification, analogous to several recent attempts at group identification using eigenvectors of the correlation matrix. All of these approaches assumed a one-to-one correspondence of dominant eigenvectors and clusters, which has however… CONTINUE READING

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