Using the modified sample entropy to detect determinism

Hong Bo Xie, Jing Yi Guo, Yongping Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)


A modified sample entropy (mSampEn), based on the nonlinear continuous and convex function, has been proposed and proven to be superior to the standard sample entropy (SampEn) in several aspects. In this Letter, we empirically investigate the ability of the mSampEn statistic combined with surrogate data method to detect determinism. The effects of the datasets length and noise on the proposed method to differentiate between deterministic and stochastic dynamics are tested on several benchmark time series. The noise performance of the mSampEn statistic is also compared with the singular value decomposition (SVD) and symplectic geometry spectrum (SGS) based methods. The results indicate that the mSampEn statistic is a robust index for detecting determinism in short and noisy time series.
Original languageEnglish
Pages (from-to)3926-3931
Number of pages6
JournalPhysics Letters, Section A: General, Atomic and Solid State Physics
Issue number38
Publication statusPublished - 23 Aug 2010


  • Deterministic chaos
  • Sample entropy
  • Stochastic process
  • Surrogate data
  • Time series

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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