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

机译:用于多变量时间序列分析的交叉和联网分区过渡网络

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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.
机译:我们提出了两个耦合系统的多变量时间序列的交叉和联合序数转换网络的构造,其中通常存在同步。特别是,我们专注于相位同步,这是动态系统中的原型情景。我们系统地表明交叉和联合序列模式过渡网络对相位同步敏感。此外,我们发现一些特殊缺失的序数模式在形成参数空间中的详细结构时起着至关重要的作用,而置换熵措施的计算通常不会。我们得出结论,交叉和联合序列分区过渡网络方法为同步转换的传统象征性分析提供了互补的见解。

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