Effect of noises on moving cut data-approximate entropy | Zendy

Hongmei Jin | Zendy; He Wen-Ping | Zendy; Wen Zhang | Zendy; Aixia Feng | Zendy; Wei Hou | Zendy

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Effect of noises on moving cut data-approximate entropy

Author(s) -

Hongmei Jin,

He Wen-Ping,

Wen Zhang,

Aixia Feng,

Wei Hou

Publication year - 2012

Publication title -

acta physica sinica

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.199

H-Index - 47

ISSN - 1000-3290

DOI - 10.7498/aps.61.129202

Subject(s) - approximate entropy , computer science , white noise , observational study , entropy (arrow of time) , additive white gaussian noise , gaussian , noise (video) , gaussian noise , forcing (mathematics) , statistics , pattern recognition (psychology) , algorithm , artificial intelligence , mathematics , physics , mathematical analysis , quantum mechanics , image (mathematics)

Affected by some factors such as external forcing and the measurement errors of instrument itself, observational data often contain noises, disturbances and some other false information. To solve this problem, the effects of different noises on moving cut data-approximate entropy (MC-ApEn) are investigated in this paper. The results indicate that MC-ApEn is little affected by random spikes and Gaussian white noise, which means that the MC-ApEn method has strong anti-noise ability. The results provide an essential experimental basis for the wide applications of the present method to observational data.

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