% This is an EMD/EEMD program
%
% function allmode=eemd(Y,Nstd,NE)
%
% INPUT:
% Y: Inputted data;
% Nstd: ratio of the standard deviation of the added noise and that of Y;
% NE: Ensemble number for the EEMD
% OUTPUT:
% A matrix of N*(m+1) matrix, where N is the length of the input
% data Y, and m=fix(log2(N))-1. Column 1 is the original data, columns 2, 3, ...
% m are the IMFs from high to low frequency, and comlumn (m+1) is the
% residual (over all trend).
%
% NOTE:
% It should be noted that when Nstd is set to zero and NE is set to 1, the
% program degenerates to a EMD program.
%
% References can be found in the "Reference" section.
%
% The code is prepared by Zhaohua Wu. For questions, please read the "Q&A" section or
% contact
% zwu@fsu.edu
%
function allmode=eemd(Y,Nstd,NE)
xsize=length(Y);
dd=1:1:xsize;
Ystd=std(Y);
Y=Y/Ystd;
TNM=fix(log2(xsize))-1;
TNM2=TNM+2;
for kk=1:1:TNM2,
for ii=1:1:xsize,
allmode(ii,kk)=0.0;
end
end
for iii=1:1:NE,
for i=1:xsize,
temp=randn(1,1)*Nstd;
X1(i)=Y(i)+temp;
end
for jj=1:1:xsize,
mode(jj,1) = Y(jj);
end
xorigin = X1;
xend = xorigin;
nmode = 1;
while nmode <= TNM,
xstart = xend;
iter = 1;
while iter<=10,
[spmax, spmin, flag]=extrema(xstart);
upper= spline(spmax(:,1),spmax(:,2),dd);
lower= spline(spmin(:,1),spmin(:,2),dd);
mean_ul = (upper + lower)/2;
xstart = xstart - mean_ul;
iter = iter +1;
end
xend = xend - xstart;
nmode=nmode+1;
for jj=1:1:xsize,
mode(jj,nmode) = xstart(jj);
end
end
for jj=1:1:xsize,
mode(jj,nmode+1)=xend(jj);
end
allmode=allmode+mode;
end
allmode=allmode/NE;
allmode=allmode*Ystd;
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