随机分形信号的二次时变Hausdorff大偏差多重分形谱

Gang Xiong, Shuning Zhang, Li Shu
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引用次数: 0

摘要

多重分形虽然描述了奇异指数的谱分布,但失去了时间信息,难以描述非平稳系统的动态演化过程。时变奇异分布反映了系统的空间动力学特性。因此,提出了时变二次多重分形谱。与Wigner-Ville时频分析类似,选取被分析信号的时滞共轭作为窗口函数,在短时多重分形分析的基础上推导出瞬时自相关的二次时奇点指数分布,即二次时奇点多重分形分布,包括Hausdorff测度、时变奇异谱分布、时变大偏差多重分形谱、给出了信号在任意时刻的奇异指数分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Quadratic Time-Varying Hausdorff and Large Deviation Multifractal Spectrum of Stochastic Fractal Signal
Although multifractal describes the spectrum distribution of Singularity Exponent (SE), it loses the temporal information, and it’s hard to describe the dynamics evolving process of non-stationary system. The time-varying singularity distribution indicates the spatial dynamics character of system. Therefore, the time-varying quadratic multifractal spectrum is proposed. Similar to the Wigner-Ville time-frequency analysis, the time-delayed conjugation of analyzed signal is selected as the windows function, and the quadratic time-singularity exponent distribution of the instantaneous self-correlation is deduced based on the short-time multifractal analysis, i.e. quadratic time-singularity multifractal distribution, which includes Hausdorff Measure, time-varying singular spectrum distribution, time-varying large deviation multifractal spectrum, which exhibits the singular exponent distribution of signal at arbitrary time.
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