Alternative Ways to Compare the Detendred Fluctuation Analysis and its Variants. Application to Visual Tunneling Detection - Archive ouverte HAL Access content directly
Journal Articles Digital Signal Processing Year : 2020

Alternative Ways to Compare the Detendred Fluctuation Analysis and its Variants. Application to Visual Tunneling Detection

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Abstract

The detrended fluctuation analysis (DFA) and its variants such as the detrended moving average (DMA) are widely used to estimate the Hurst exponent. These methods are very popular as they do not require advanced skills in the field of signal processing and statistics while providing accurate results. As a consequence, a great deal of interest has been paid to compare them and to better understand their behaviors from a mathematical point of view. In this paper, our contribution is threefold. Firstly, we propose another variant avoiding the discontinuities between consecutive local trends of the DFA by a priori constraining them to be continuous. Secondly, we show that, in all these approaches, the square of the fluctuation function can be presented in a similar matrix form. When the process is wide-sense stationary (w.s.s.), the latter can be seen as the power of the output of a linear filtering whose frequency response depends on the given method. In the general case, an interpretation of the square of the fluctuation function is also given by expressing it as the convolution between the 2D-Fourier transform of two matrices, one whose elements correspond to the instantaneous correlation function of the signal and the other which depends on the detrending method. To end up, an illustration is provided in the field of avionics for the detection of the visual tunneling, a deleterious cognitive state.

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Dates and versions

hal-02940122 , version 1 (21-11-2022)

Licence

Attribution - NonCommercial - CC BY 4.0

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Bastien Berthelot, Eric Grivel, Pierrick Legrand, Jean-Marc André, Patrick Mazoyer. Alternative Ways to Compare the Detendred Fluctuation Analysis and its Variants. Application to Visual Tunneling Detection. Digital Signal Processing, 2020, ⟨10.1016/j.dsp.2020.102865⟩. ⟨hal-02940122⟩
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