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Cross and joint ordinal partition transition networks for multivariate time series analysis

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Abstract

We propose the construction of cross and joint ordinal pattern transition networks from multivariate time series for two coupled systems, where synchronizations are often present. In particular, we focus on phase synchronization, which is a prototypical scenario in dynamical systems. We systematically show that cross and joint ordinal pattern transition networks are sensitive to phase synchronization. Furthermore, we find that some particular missing ordinal patterns play crucial roles in forming the detailed structures in the parameter space, whereas the calculations of permutation entropy measures often do not. We conclude that cross and joint ordinal partition transition network approaches provide complementary insights into the traditional symbolic analysis of synchronization transitions.

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Acknowledgements

This work was in part financially sponsored by the Natural Science Foundation of Shanghai (Grant No. 17ZR1444800 and 18ZR1411800).

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  1. Department of Physics, East China Normal University, Shanghai, 200062, China

    Heng Guo, Jia-Yang Zhang, Yong Zou & Shu-Guang Guan

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  1. Heng Guo
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Correspondence to Yong Zou or Shu-Guang Guan.

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Guo, H., Zhang, JY., Zou, Y. et al. Cross and joint ordinal partition transition networks for multivariate time series analysis. Front. Phys. 13, 130508 (2018). https://doi.org/10.1007/s11467-018-0805-0

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