extractimf {EMD} | R Documentation |
This function extracts intrinsic mode function from given a signal.
extractimf(residue, tt=NULL, tol=sd(residue)*0.1^2, max.sift=20, stoprule="type1", boundary="periodic", sm="none", spar=NA, weight=20, check=FALSE)
residue |
observation or signal observed at time tt |
tt |
observation index or time index |
tol |
tolerance for stopping rule of sifting |
max.sift |
the maximum number of sifting |
stoprule |
stopping rule of sifting |
boundary |
specifies boundary condition from ``none", ``wave", ``symmetric", ``periodic" or ``evenodd". |
sm |
specifies whether envelop is constructed by smoothing spline. |
spar |
specifies user-supplied smoothing parameter of spline. |
weight |
the smoothness of spline is determined by weight times smoothing parameter of GCV. |
check |
specifies whether the sifting process is displayed. If check=TRUE , click the plotting area to start the next step. |
This function extracts intrinsic mode function from given a signal.
imf |
imf |
residue |
residue signal after extracting the finest imf from residue |
niter |
the number of iteration to obtain the imf |
Huang, N. E., Shen, Z., Long, S. R., Wu, M. L. Shih, H. H., Zheng, Q., Yen, N. C., Tung, C. C. and Liu, H. H. (1998) The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis. Proceedings of the Royal Society London A, 454, 903–995.
### Generating a signal ndata <- 3000 X11(); par(mfrow=c(1,1), mar=c(1,1,1,1)) tt2 <- seq(0, 9, length=ndata) xt2 <- sin(pi * tt2) + sin(2* pi * tt2) + sin(6 * pi * tt2) + 0.5 * tt2 plot(tt2, xt2, xlab="", ylab="", type="l", axes=FALSE); box() ### Extracting the first IMF by sifting process tryimf <- extractimf(xt2, tt2, check=FALSE)