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: 雜誌貢獻文章

89 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)5865-5873
頁數9
期刊Physica A: Statistical Mechanics and its Applications
392
發行號23
DOIs
出版狀態已發佈 - 2013 十二月 1

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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