Modified multiscale entropy for short-term time series analysis

Shuen De Wu, Chiu Wen Wu, Kung Yen Lee, Shiou Gwo Lin*


研究成果: 雜誌貢獻期刊論文同行評審

173 引文 斯高帕斯(Scopus)


Multiscale entropy (MSE) is a prevalent algorithm used to measure the complexity of a time series. Because the coarse-graining procedure reduces the length of a time series, the conventional MSE algorithm applied to a short-term time series may yield an imprecise estimation of entropy or induce undefined entropy. To overcome this obstacle, the modified multiscale entropy (MMSE) was developed. The coarse-graining procedure was replaced with a moving-average procedure and a time delay was incorporated for constructing template vectors in calculating sample entropy. For conducting short-term time series analysis, this study shows that the MMSE algorithm is more reliable than the conventional MSE.

頁(從 - 到)5865-5873
期刊Physica A: Statistical Mechanics and its Applications
出版狀態已發佈 - 2013 12月 1

ASJC Scopus subject areas

  • 統計與概率
  • 凝聚態物理學


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