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Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

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  • Qingju Fan
  • Yonghong Wu

Abstract

In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Qingju Fan & Yonghong Wu, 2015. "Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(8), pages 1-6, August.
    • Handle: RePEc:spr:eurphb:v:88:y:2015:i:8:p:1-6:10.1140/epjb/e2015-60332-x
    DOI: 10.1140/epjb/e2015-60332-x
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    Statistical and Nonlinear Physics;

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