Extremal-point density of scaling processes from fractal Brownian motion to turbulence in one dimension
Yongxiang Huang, Lipo Wang, F.G. Schmitt, Xiaobo Zheng, Nan Jiang,, Yulu Liu

TL;DR
This paper investigates the distribution of local extrema in scaling processes like fractional Brownian motion and turbulence, revealing how extremal point density relates to scaling exponents and intermittency.
Contribution
It systematically analyzes extremal point density in synthesized and experimental turbulence data, linking it to scaling exponents and intermittency effects.
Findings
Measured extremal point density matches theoretical predictions for fBm.
Intermittency correction does not alter extremal point distribution, only amplitude.
Scaling exponents derived from EPD align with known turbulence regimes.
Abstract
In recent years several local extrema based methodologies have been proposed to investigate either the nonlinear or the nonstationary time series for scaling analysis. In the present work we study systematically the distribution of the local extrema for both synthesized scaling processes and turbulent velocity data from experiments. The results show that for the fractional Brownian motion (fBm) without intermittency correction the measured extremal point density (EPD) agrees well with a theoretical prediction. For a multifractal random walk (MRW) with the lognormal statistics, the measured EPD is independent with the intermittency parameter , suggesting that the intermittency correction does not change the distribution of extremal points, but change the amplitude. By introducing a coarse-grained operator, the power-law behavior of these scaling processes is then revealed via the…
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