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在去趋势波动分析和傅里叶分析之间建立直接联系。

Establishing a direct connection between detrended fluctuation analysis and Fourier analysis.

作者信息

Kiyono Ken

机构信息

Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Oct;92(4):042925. doi: 10.1103/PhysRevE.92.042925. Epub 2015 Oct 29.

Abstract

To understand methodological features of the detrended fluctuation analysis (DFA) using a higher-order polynomial fitting, we establish the direct connection between DFA and Fourier analysis. Based on an exact calculation of the single-frequency response of the DFA, the following facts are shown analytically: (1) in the analysis of stochastic processes exhibiting a power-law scaling of the power spectral density (PSD), S(f)∼f(-β), a higher-order detrending in the DFA has no adverse effect in the estimation of the DFA scaling exponent α, which satisfies the scaling relation α=(β+1)/2; (2) the upper limit of the scaling exponents detectable by the DFA depends on the order of polynomial fit used in the DFA, and is bounded by m+1, where m is the order of the polynomial fit; (3) the relation between the time scale in the DFA and the corresponding frequency in the PSD are distorted depending on both the order of the DFA and the frequency dependence of the PSD. We can improve the scale distortion by introducing the corrected time scale in the DFA corresponding to the inverse of the frequency scale in the PSD. In addition, our analytical approach makes it possible to characterize variants of the DFA using different types of detrending. As an application, properties of the detrending moving average algorithm are discussed.

摘要

为了理解使用高阶多项式拟合的去趋势波动分析(DFA)的方法学特征,我们建立了DFA与傅里叶分析之间的直接联系。基于对DFA单频响应的精确计算,通过分析得出以下事实:(1)在分析呈现功率谱密度(PSD)幂律标度S(f)∼f^(-β)的随机过程时,DFA中的高阶去趋势对DFA标度指数α的估计没有不利影响,α满足标度关系α=(β + 1)/2;(2)DFA可检测到的标度指数上限取决于DFA中使用的多项式拟合阶数,并受m + 1限制,其中m是多项式拟合的阶数;(3)DFA中的时间尺度与PSD中相应频率之间的关系会因DFA的阶数和PSD的频率依赖性而扭曲。我们可以通过在DFA中引入与PSD中频率尺度倒数相对应的校正时间尺度来改善尺度扭曲。此外,我们的分析方法使得使用不同类型去趋势来表征DFA的变体成为可能。作为应用,讨论了去趋势移动平均算法的性质。

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