Empirical Mode Decomposition Toolbox

            Toolbox for Empirical Mode Decomposition of 1-D, 2-D and more dimensional
signals.

Summary from Wikipedia (http://en.wikipedia.org/wiki/Hilbert-Huang_transform):

Using the EMD method, any complicated data set can be decomposed into a finite
and often small number of components, which is a collection of intrinsic mode
functions (IMF). An IMF represents a generally simple oscillatory mode as a
counterpart to the simple harmonic function. By definition, an IMF is any
function with the same number of extrema  and zero crossings, with its envelopes
being symmetric with respect to zero. The definition of an IMF guarantees a
well-behaved Hilbert transform of the IMF. This decomposition method operating
in the time domain is adaptive  and highly efficient. Since the decomposition is
based on the local characteristic time scale of the data, it can be applied to
nonlinear and nonstationary processes.

Changelog
--------------
1.4  - bugfixes under scilab 6.1

1.3  - several bugfixes
     - emd_instfreq added
     - io, rmtag, addtag, findtag, peaks, local_peaks, zero_crossing, dirstretch
have now emd_ as prefix
     - help pages and demos fixed

1.2  - works under scilab 5.4

1.1  - some Bugs are removed
     - help chapter are added

1.0  Initial release