Fast Ensemble Empirical Mode Decomposition Using the Savitzky Golay filter

Abstract

Empirical mode decomposition (EMD) is a powerful algorithm proposed to analysis of nonlinear and non-stationary signals. The phenomenon of mode mixing is one of the major disadvantages of the EMD. The Ensemble EMD (EEMD) was introduced to eliminate the mode-mixing effect. The principle of EEMD is to add additional white noise into the signal with many trials. The noise in each trial is different; and the added noise can be completely cancelled out on average, if the number of trials is very high. The number of trials is a high computational load. The improvement on computational efficiency of EEMD is therefore required. In this paper, an improvement on the computing time of the EEMD was proposed by replacing white noise with white noise filtered using Savitzky-Golay (SG) filter. Numerical simulations were performed to demonstrate that such replacement has effectively reduced the number of trials to obtain a noise-free reconstructed signal.