Title :
Empirical mode decomposition, fractional Gaussian noise and Hurst exponent estimation
Author :
Rilling, Gabriel ; Flandrin, Patrick ; Goncalves, Paulo
Author_Institution :
Lab. de Phys., Ecole Normale Superieure de Lyon, France
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.
Keywords :
Gaussian noise; adaptive signal processing; gamma distribution; spectral analysis; statistical analysis; EMD; Hurst exponent estimation; adaptive decomposition; broadband noise model; empirical mode decomposition; equivalent filter bank structure; fractional Gaussian noise; gamma distributed variances; scaling exponents; spectral analysis; statistical characterization; wavelet decomposition properties; 1f noise; Character generation; Filter bank; Frequency; Gaussian noise; Nonlinear systems; Signal design; Signal processing; Spectral analysis; Wavelet analysis;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1416052