On the behavior of EMD and MEMD in presence of symmetric alpha-stable noise
Language
en
Article de revue
This item was published in
IEEE Signal Processing Letters. 2015-07, vol. 22, n° 7, p. 818-822
Institute of Electrical and Electronics Engineers
English Abstract
EmpiricalMode Decomposition (EMD) and its extended versions such as Multivariate EMD (MEMD) are data-driven techniques that represent nonlinear and non-stationary data as a sum of a finite zero-mean AM-FM components referred ...Read more >
EmpiricalMode Decomposition (EMD) and its extended versions such as Multivariate EMD (MEMD) are data-driven techniques that represent nonlinear and non-stationary data as a sum of a finite zero-mean AM-FM components referred to as Intrinsic Mode Functions (IMFs). The aim of this work is to analyze the behavior of EMD and MEMD in stochastic situations involving non-Gaussian noise, more precisely, we examine the case of Symmetric Alpha-Stable noise. We report numerical experiments supportingthe claim that both EMD and MEMD act, essentially, as filter banks on each channel of the input signal in the case of Symmetric Alpha Stable noise. Reported results show that, unlike EMD, MEMD has the ability to align common frequency modes across multiple channels in same index IMFs. Further, simulations show that, contrary to EMD, for MEMD the stability property is well satisfied for the modes of lower indices and this result is exploited for the estimation of the stability index of the Symmetric Alpha Stable input signal.Read less <
English Keywords
EMD
Estimation
filter banks
Frequency measurement
Gaussian distribution
MEMD
Noise
Stability criteria
symmetric $alpha$–stable noise
Origin
Hal imported