computes Empirical Mode Decomposition
[IMF,NB_ITERATIONS]=emdc(T,X); [IMF,NB_ITERATIONS]=emdc([],X; [IMF,NB_ITERATIONS]=emdc(T,X,STOP_PARAMETERS); [IMF,NB_ITERATIONS]=emdc(T,X,STOP_PARAMETERS,MAX_IMFS);
sampling times. If T=[], the signal is assumed uniformly sampled. 1xN time instants
analyzed signal, 1xN signal data
parameters for the stopping criterion: if scalar the value is used to specify THRESHOLD only. otherwise the vector should be: [THRESHOLD,TOLERANCE]. if STOP_PARAMETERS is unspecified or empty, default values are used: [0.05,0.05]
maximum number of IMFs to be extracted. If MAX_IMFS is zero, empty or unspecified, the default behavior is to extract as many IMFs as possible.
intrinsic mode functions (IMFs) (last line = residual)
effective number of sifting iterations for each mode
computes EMD according to [1] with stopping criterion for sifting in [2]:
mean of boolean array {(mean_amplitude)/(envelope_amplitude) > THRESHOLD} < TOLERANCE & |#zeros-#extrema|<=1
[1] N. E. Huang et al., "The empirical mode decomposition and the
Hilbert spectrum for non-linear and non stationary time series analysis",
Proc. Royal Soc. London A, Vol. 454, pp. 903-995, 1998
[2] G. Rilling, P. Flandrin and P. Gonçalves
"On Empirical Mode Decomposition and its algorithms",
IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing
NSIP-03, Grado (I), June 2003