Toolbox for Empirical Mode Decomposition of 1-D, 2-D and more dimensional
signals.
Summary from Wikipedia (http://en.wikipedia.org/wiki/Hilbert%E2%80%93Huang_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.
