Advances in Empirical Mode Decomposition for computing Instantaneous Amplitudes and Instantaneous Frequencies

Abstract

In this paper, we propose improvements to the Complete Ensemble Empirical Mode Decomposition (CEEMD) aimed at the resolution of closely-spaced Intrinsic Mode Functions (IMFs), reproducible and consistent decompositions, reduction in estimation error, numerical stability, and faster decompositions through fewer ensemble trials. We focus on three areas to achieve these goals: 1) use of complimentary masking signals applied at the IMF level, 2) use of narrowband tones instead of white noise for masking signals, and 3) ensuring a true IMF is obtained after ensemble averaging. We propose a numerically stable Instantaneous Frequency (IF) demodulation approach that together with a previously-reported Instantaneous Amplitude (IA) demodulation, allows estimation of the IA/IF parameters of the IMFs and hence a time-frequency representation. Using biomedical signal examples, we compare our results with CEEMD and Improved CEEMD (ICEEMD).