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高维分形和多重分形的去趋势波动分析

Detrended fluctuation analysis for fractals and multifractals in higher dimensions.

作者信息

Gu Gao-Feng, Zhou Wei-Xing

机构信息

School of Business, East China University of Science and Technology, Shanghai 200237, China.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Dec;74(6 Pt 1):061104. doi: 10.1103/PhysRevE.74.061104. Epub 2006 Dec 7.

Abstract

One-dimensional detrended fluctuation analysis (DFA) and multifractal detrended fluctuation analysis (MFDFA) are widely used in the scaling analysis of fractal and multifractal time series because they are accurate and easy to implement. In this paper we generalize the one-dimensional DFA and MFDFA to higher-dimensional versions. The generalization works well when tested with synthetic surfaces including fractional Brownian surfaces and multifractal surfaces. The two-dimensional MFDFA is also adopted to analyze two images from nature and experiment, and nice scaling laws are unraveled.

摘要

一维去趋势波动分析(DFA)和多重分形去趋势波动分析(MFDFA)因其准确且易于实现,而被广泛应用于分形和多重分形时间序列的标度分析。在本文中,我们将一维DFA和MFDFA推广到了高维版本。在用包括分数布朗曲面和多重分形曲面在内的合成曲面进行测试时,这种推广效果良好。二维MFDFA还被用于分析两幅自然图像和实验图像,并揭示了良好的标度律。

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