Detrended fluctuation analysis of power-law-correlated sequences with random noises

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dc.creatorTadaki, Shin-ichi
dc.date2009-02-04
dc.date.accessioned2026-07-07T12:37:34Z
dc.date.available2026-07-07T12:37:34Z
dc.descriptionImprovement in time resolution sometimes introduces short-range random noises into temporal data sequences. These noises affect the results of power-spectrum analyses and the Detrended Fluctuation Analysis (DFA). The DFA is one of useful methods for analyzing long-range correlations in non-stationary sequences. The effects of noises are discussed based on artificial temporal sequences. Short-range noises prevent power-spectrum analyses from detecting long-range correlations. The DFA can extract long-range correlations from noisy time sequences. The DFA also gives the threshold time length, under which the noises dominate. For practical analyses, coarse-grained time sequences are shown to recover long-range correlations.
dc.description12 pages, 11 figures
dc.identifierhttps://arxiv.org/abs/0902.0678
dc.identifierhttp://arxiv.org/abs/0902.0678
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/218486
dc.subjectData Analysis, Statistics and Probability
dc.subjectPhysics and Society
dc.titleDetrended fluctuation analysis of power-law-correlated sequences with random noises
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