EEMD family, Matlab version. PARFOR supported.
matlabpool open 8 to enable parallel computing.
Empirical mode decomposition. No ensemble, no additional white noise.
c = emd(y, goal)
y: one-dimensional input data
goal: target mode numbers to decompose
Ensemble empirical mode decomposition.
modes = eemd(y, goal, ens, nos)
Please note if you are running with a 64-bit Windows PC, Matlab will automatically run with
eemd.mexw64 instead of this script.
modes = eemd2(img, goal, ens, nos_wn) [modes, G, D] = eemd2(img, goal, ens, nos_wn)
modes = eemd3(img, goal, ens, nos_wn) [modes, O, P, Q] = eemd3(img, goal, ens, nos_wn)
Running this file will give you decomposed modes of a 64x64 Lena image.
Running this file will decompose a 54x54x54 volume of a Mimivirus. Please be carful as running this demo will cost up to 20 GB memory.
mex -IC:/path/to/boost_1_55_0 cpp/eemd.cpp
C:/path/to/boost_1_55_0 with path to Boost on your computer.