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Empirical study of the scaling behavior of the amplitude-frequency distribution of the Hilbert-Huang transform and its application in sunspot time series analysis

机译:Hilbert-Huang变换幅度-频率分布的标度行为的经验研究及其在黑子时间序列分析中的应用

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摘要

Investigating long-range correlation by the Hurst exponent, H, is crucial in the study of time series. Recently, empirical-mode-decomposition-based arbitrary-order Hilbert spectral analysis (EMD-HSA) has been proposed to numerically obtain without proof a scaling relationship, generated from the amplitude-frequency distribution, related to H. We propose a formalism to empirically study EMD-HSA, to deduce its scaling exponent ξ(q) from the perspective of EMD-based arbitrary-order Hilbert marginal spectrum (EMD-HMS), and to numerically compare the results with the expected H. EMD-HSA and EMD-HMS experiments show that, by incompletely removing (quasi-)periodic trends, the sunspot series should have an H value around 0.12.
机译:在时间序列的研究中,用赫斯特指数H进行远距离相关性研究至关重要。最近,有人提出了基于经验模式分解的任意阶希尔伯特频谱分析(EMD-HSA),以数值方式获得与H相关的由振幅-频率分布产生的比例关系。研究EMD-HSA,从基于EMD的任意阶希尔伯特边际谱(EMD-HMS)的角度推导其标度指数ξ(q),并将结果与​​预期的H进行数值比较。EMD-HSA和EMD- HMS实验表明,通过不完全消除(准)周期性趋势,黑子序列的H值应约为0.12。

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