用于多元时间序列分析的交叉和联合有序划分转移网络
Cross and joint ordinal partition transition networks for multivariate time series analysis
摘要：
我们建议从两个耦合系统的多变量时间序列中构建交叉和联合有序模式转换网络，其中通常存在同步。特别是，我们专注于相位同步，这是动力系统中的原型场景之一。我们系统地表明，交叉和联合有序模式转换网络是敏感的相位同步。此外，我们发现，一些特定的丢失的有序模式在形成参数空间中的详细结构中起着至关重要的作用，而排列熵测度的计算往往没有。我们的结论是，交叉和联合有序分区过渡网络的方法提供了互补的见解，传统的符号分析同步过渡。
英文摘要：
We propose to construct 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 one of prototypical scenarios in dynamical systems. We systematically show that cross and joint ordinal patterns 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 to the traditional symbolic analysis of synchronization transitions.
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