Different number of modes while performing the EEMD (Ensembled Empirical Mode Decomposition) I am performing an Ensemble Empirical Mode Decomposition (EEMD).
I wrote a MATLAB routine to perform the EMD. I noticed that when adding white Gaussian noise to the input signal, sometimes I obtain a different number of modes, even if the noise variance is not so high. Clearly, if this happens, I cannot sum compute consistent ensemble-averages for each mode.
Do you think this depends more on the nature of the input signal or on my EMD algorithm/routine?
It depends on both on the signal content and on the EMD implementation. EMD can be sensitive to time shifts, especially with strong transients, to noise power. Robust or constrained EMD on single signal or multivariate signals have been developed.
Your question relates to signal morphology, processing purpose, and quality metrics. I doubt they can be answered globally.