Empirical Mode Decomposition, fractional Gaussian noise and Hurst exponent estimation

Abstract

Huang's data-driven technique of empirical mode decomposition (EMD) is applied to the versatile, broadband, model of fractional Gaussian noise (fGn). The spectral analysis and statistical characterization of the obtained modes reveal an equivalent filter bank structure together with gamma distributed variances, both sharing some properties with wavelet decompositions. These common features are then used to mimic wavelet based techniques aimed at estimating the Hurst exponent.