物理学报2024，Vol.73Issue(11)：10-19,10.DOI:10.7498/aps.73.20231133
一种无偏差的多通道多尺度样本熵算法
Unbiased multivariate multiscale sample entropy
摘要
Abstract
The development of multi-channel data acquisition techniques has provided richer prior information for studying the nonlinear dynamic characteristics of complex systems.However,conventional nonlinear feature extraction algorithms prove unsuitable in the context of multi-channel data.Previously,the multivariate multiscale sample entropy(MMSE)algorithm was introduced for multi-channel data analysis.Although the MMSE algorithm generalized the multiscale sample entropy algorithm,presenting a novel method for multidimensional data analysis,it remains deficient in theoretical underpinning and suffers from shortcomings,such as missing cross-channel correlation information and having biased estimation results.In this paper,unbiased multivariate multiscale sample entropy algorithm(UMMSE)is proposed.UMMSE increases the embedding dimension from M to M+p.This increasing strategy facilitates the reconstruction of a deterministic phase space.By virtue of theoretical scrutiny grounded in probability theory and subsequent experimental validation,this paper illustrates the algorithm's effectiveness in extracting inter-channel correlation information through the integration of cross-channel conditional probabilities.The computation of similarities between sample points across different channels is recognized as a potential source of bias and instability in algorithms.Through simulation experiments,this study delineates the parameter selection range for the UMMSE algorithm.Subsequently,diverse simulation signals are employed to showcase the UMMSE algorithm's efficacy in extracting both within-channel and cross-channel correlation information.Ultimately,this paper demonstrates that the new algorithm has the lowest computational cost compared with traditional MMSE algorithms.关键词
非线性动力学/多通道数据/多通道多尺度样本熵Key words
nonlinear dynamics/multi-channel signal/multivariate multiscale sample entropy引用本文复制引用
李惟嘉,申晓红,李亚安..一种无偏差的多通道多尺度样本熵算法[J].物理学报,2024,73(11):10-19,10.基金项目
国家自然科学基金(批准号:11874302,62031021)资助的课题. Project supported by the National Natural Science Foundation of China(Grant Nos.11874302,62031021). （批准号:11874302,62031021）
