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Alternative TitleError Assessment in Modeling with Fractal Brownian Motions
Source PublicationFRACTALS
Other AbstractTo model a given time series $F(t)$ with fractal Brownian motions (fBms), it is necessary to have appropriate error assessment for related quantities. Usually the fractal dimension $D$ is derived from the Hurst exponent $H$ via the relation $D=2-H$, and the Hurst exponent can be evaluated by analyzing the dependence of the rescaled range $\langle|F(t+\tau)-F(t)|\rangle$ on the time span $\tau$. For fBms, the error of the rescaled range not only depends on data sampling but also varies with $H$ due to the presence of long term memory. This error for a given time series then can not be assessed without knowing the fractal dimension. We carry out extensive numerical simulations to explore the error of rescaled range of fBms and find that for $0
Subject Area天文和天体物理
Document Type期刊论文
Corresponding Authorliusiming
Recommended Citation
GB/T 7714
liusiming. 分形布朗运动建模中的误差分析[J]. FRACTALS,2013,21(4):1-6.
APA liusiming.(2013).分形布朗运动建模中的误差分析.FRACTALS,21(4),1-6.
MLA liusiming."分形布朗运动建模中的误差分析".FRACTALS 21.4(2013):1-6.
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