extractimf {EMD}R Documentation

Intrinsic Mode Function

Description

This function extracts intrinsic mode function from given a signal.

Usage

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)

Arguments

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.

Details

This function extracts intrinsic mode function from given a signal.

Value

imf imf
residue residue signal after extracting the finest imf from residue
niter the number of iteration to obtain the imf

References

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.

See Also

extrema, emd.

Examples

### 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)

[Package EMD version 1.2.0 Index]