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Article Dans Une Revue Review of Scientific Instruments Année : 2017

Estimating two-point statistics from derivatives of a signal containing noise: Application to auto-correlation functions of turbulent Lagrangian tracks

Résumé

This article describes a method for calculating moments and correlation functions of signal derivatives, which were rid of experimental noise without the use of filtering operations. The method is based on the computation of the ensemble-average of different time (or spatial) increments of the signal. The hypotheses are that the noise is white and not correlated with the signal; however, the method is also shown to work with colored noise. The method is first developed, considering white noise, and benchmarked with synthetic trajectories containing noise with variable signal-to-noise ratios. It is then tested on experimental trajectories in the context of Lagrangian tracking of particles in turbulent flows, either containing a short-correlated noise or a colored noise. Published by AIP Publishing.
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Dates et versions

hal-02519255 , version 1 (25-03-2020)

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Nathanaël Machicoane, P D Huck, R. Volk. Estimating two-point statistics from derivatives of a signal containing noise: Application to auto-correlation functions of turbulent Lagrangian tracks. Review of Scientific Instruments, 2017, 88, ⟨10.1063/1.4986467⟩. ⟨hal-02519255⟩
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