emd.sift.stop_imf_rilling#
- emd.sift.stop_imf_rilling(upper_env, lower_env, sd1=0.05, sd2=0.5, tol=0.05, niters=None)[source]#
Compute the Rilling et al 2003 sift stopping metric.
This metric tries to guarantee globally small fluctuations in the IMF mean while taking into account locally large excursions that may occur in noisy signals.
- Parameters:
- upper_envndarray
The upper envelope of a proto-IMF
- lower_envndarray
The lower envelope of a proto-IMF
- sd1float
The maximum threshold for globally small differences from zero-mean
- sd2float
The maximum threshold for locally large differences from zero-mean
- tolfloat (0 < tol < 1)
(1-tol) defines the proportion of time which may contain large deviations from zero-mean
- nitersint
Number of sift iterations currently completed
- Returns:
- bool
A flag indicating whether to stop siftingg
- float
The SD metric value
Notes
This method is described in section 3.2 of: Rilling, G., Flandrin, P., & Goncalves, P. (2003, June). On empirical mode decomposition and its algorithms. In IEEE-EURASIP workshop on nonlinear signal and image processing (Vol. 3, No. 3, pp. 8-11). NSIP-03, Grado (I). http://perso.ens-lyon.fr/patrick.flandrin/NSIP03.pdf