排列熵主要用于机械故障诊断以及脑电图等方面。We introduce complexity parameters for time series based on comparison of neighboring values. The definition directly applies to arbitrary real–world data. For some well–known chaotic dynamical systems it is shown that our compl
计算数据矩阵中面向列向量的多尺度、多变量排列熵。多变量排列熵是一种考虑多个数据向量之间相关性的方法（例如EEG、ERP、ECG、fMRI等）。有关详细信息，请参阅Morabito FC, Labate D, La Foresta F, Bramanti A, Morabito G, Palamara I. Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG.
