Open AccessEffect of noises on moving cut data-approximate entropy
Author(s) -
Hongmei Jin,
Wenping He,
Wen Zhang,
Ao Feng,
Hou Wei
Publication year - 2012
Publication title -
wuli xuebao
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.