近似熵、互近似熵的性质、快速算法及其在脑电与认知研究中的初步应用

ApEn and Cross-ApEn: Property, Fast Algorithm and Preliminary Application to the Study of EEG and Cognition

本文从信号处理的角度介绍了近似嫡、互近似熵的概念、性质与应用，并给出了一种计算近似熵、互近似熵的实用快速算法．本文还通过实际算例说明了近似烟在表征信号的复杂性、互近似熵在表征信号的模式相似性方面的能力及其在脑电与认知研究中的初步应用。

The conception, properties and application of approxiamte entropy (ApEn) and cross approximate entropy (Cross--ApEn) are discussed from the view of signal proessing, and a practical fast algorithm is introduced. Several examples are employed to evaluate the potential application of ApEn to quantifying the complexity and Cross--ApEn to quantifying the pattern similarity of time series. Some initial results of its application to the study of EEG and cognition are given.