论文标题
行李振荡器中的顺序模式：分析表征的能力
Ordinal Patterns in the Duffing Oscillator: Analyzing Powers of Characterization
论文作者
论文摘要
序数模式是一种时间序列数据分析工具，用作构造置换熵的初步步骤，该步骤本身允许动态表征与混乱或常规的术语相同的特征，例如诸如Lyapunov指数之类的更理论构造。但是，与置换熵或Lyapunov指数相比，严格存储的信息严格存储更多的信息。我们提出了与行李振荡器一起工作的结果，表明有序模式反映了其他度量，甚至排列熵的动态对称性变化。我们发现，以给定参数值的对称性变化与相邻参数的稳定性变化相关，这表明该分析技术具有新颖的预测能力。
Ordinal Patterns are a time-series data analysis tool used as a preliminary step to construct the Permutation Entropy which itself allows the same characterization of dynamics as chaotic or regular as more theoretical constructs such as the Lyapunov exponent. However ordinal patterns store strictly more information than Permutation Entropy or Lyapunov exponents. We present results working with the Duffing oscillator showing that ordinal patterns reflect changes in dynamical symmetry invisible to other measures, even Permutation Entropy. We find that these changes in symmetry at given parameter values are correlated with a change in stability at neighboring parameters which suggests a novel predictive capability for this analysis technique.
