View source: R/empirical_mode_decomposition.R
CEEMD | R Documentation |
This function implements the complete ensemble empirical mode decomposition (CEEMD) algorithm.
CEEMD(sig, tt, noise.amp, trials, verbose = TRUE,
spectral.method = "arctan", diff.lag = 1, tol = 5, max.sift = 200,
stop.rule = "type5", boundary = "wave", sm = "none",
smlevels = c(1), spar = NULL, max.imf = 100, interm = NULL,
noise.type = "gaussian", noise.array = NULL)
sig |
a time series to be decomposed (vector) |
tt |
The sample times of |
noise.amp |
Amplitude of white noise to use in denoising algorithm |
trials |
Number of times to run EMD |
verbose |
If TRUE, notify when each trial is complete |
spectral.method |
See |
diff.lag |
See |
tol |
See |
max.sift |
See |
stop.rule |
See |
boundary |
See |
sm |
See |
smlevels |
See |
spar |
See |
max.imf |
See |
interm |
See |
noise.type |
If unspecified or |
noise.array |
If |
This function performs the complete ensemble empirical mode decomposition, a noise assisted empirical mode decomposition algorithm. The CEEMD works by adding a certain amplitude of white noise to a time series, decomposing it via EMD, and saving the result. In contrast to the Ensemble Empirical Mode Decomposition (EEMD) method, the CEEMD also ensures that the IMF set is quasi-complete and orthogonal. The CEEMD can ameliorate mode mixing and intermittency problems. Keep in mind that the CEEMD is a computationally expensive algorithm and may take significant time to run.
ceemd.result |
The final result of the CEEMD algorithm |
.
Daniel Bowman danny.c.bowman@gmail.com
Torres, M. E., Colominas, M. A., Schlotthauer, G., Flandrin, P. (2011). A complete ensemble empirical mode decomposition with adaptive noise. 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.4144-4147, doi: 10.1109/ICASSP.2011.5947265.
EEMD
, Sig2IMF
, PlotIMFs
.
## Not run:
data(PortFosterEvent)
noise.amp <- 6.4e-07
trials <- 100
ceemd.result <- CEEMD(sig, tt, noise.amp, trials)
PlotIMFs(ceemd.result, imf.list = 1:6, time.span = c(5, 10))
## End(Not run)
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