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%Function for CEEMDAN
%WARNING: for this code works it is necessary to include in the
same%directoy the file emd.m developed by Rilling and
Flandrin.%This file is available at
%http://perso.ens-lyon.fr/patrick.flandrin/emd.html%We use the
default stopping criterion.%We use the last modification:
3.2007
% Syntax
%modes=ceemdan(x,Nstd,NR,MaxIter,SNRFlag)%[modes
its]=ceemdan(x,Nstd,NR,MaxIter,SNRFlag)
% Description
%OUTPUT%modes: contain the obtained modes in a matrix with the
rows being the modes
%its: contain the sifting iterations needed for each mode for
each realization (
one row for each realization)
%INPUT%x: signal to decompose%Nstd: noise standard deviation%NR:
number of realizations%MaxIter: maximum number of sifting
iterations allowed.%SNRFlag: if equals 1, then the SNR increases
for every stage, as in [1].% If equals 2, then the SNR is the same
for all stages, as in [2].
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
The current is an improved version, introduced in:
%[1] Colominas MA, Schlotthauer G, Torres ME. "Improve complete
ensemble EMD: Asuitable tool for biomedical signal processing"%
Biomedical Signal Processing and Control vol. 14 pp. 19-29
(2014)
%The CEEMDAN algorithm was first introduced at ICASSP 2011,
Prague, Czech Republic
%The authors will be thankful if the users of this code
reference the work%where the algorithm was first presented:
%[2] Torres ME, Colominas MA, Schlotthauer G, Flandrin P. "A
Complete Ensemble E
mpirical Mode Decomposition with Adaptive Noise"% Proc. 36th
Int. Conf. on Acoustics, Speech and Signa Processing ICASSP 2011
(May 22-27, Prague, Czech Republic)
%Author: Marcelo A. Colominas%contact:
[email protected]%Last version: 25 feb
2015%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function
[modes,its]=ceemdan(x,Nstd,NR,MaxIter,SNRFlag)x=x(:)';desvio_x=std(x);
x=x/desvio_x;
modes=zeros(size(x));
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temp=zeros(size(x));aux=zeros(size(x));iter=zeros(NR,round(log2(length(x))+5));
for i=1:NR white_noise{i}=randn(size(x));%creates the
noise realizationsend;
for i=1:NR
modes_white_noise{i}=emd(white_noise{i});%calculates the modes of
white gaussian noiseend;
for i=1:NR %calculates the first mode
xi=x+Nstd*modes_white_noise{i}(1,:)/std(modes_white_noise{i}(1,:));
[temp, o, it]=emd(xi,'MAXMODES',1,'MAXITERATIONS',MaxIter);
temp=temp(1,:); aux=aux+(xi-temp)/NR; iter(i,1)=it;
end;
modes= x-aux; %saves the first modemedias =
aux;k=1;aux=zeros(size(x));es_imf =
min(size(emd(medias(end,:),'MAXMODES',1,'MAXITERATIONS',MaxIter)));
while es_imf>1 %calculates the rest of the modes for
i=1:NR tamanio=size(modes_white_noise{i}); if
tamanio(1)>=k+1 noise=modes_white_noise{i}(k+1,:);
if SNRFlag == 2 noise=noise/std(noise); %adjust the
std of the noise end; noise=Nstd*noise; try
[temp,o,it]=emd(medias(end,:)+std(medias(end,:))*noise,'MAXMODES',1,'MAXITERATIONS',MaxIter);
catch
it=0; disp('catch 1 '); disp(num2str(k))
temp=emd(medias(end,:)+std(medias(end,:))*noise,'MAXMODES',1,'MAXITERATIONS',MaxIter);
end; temp=temp(end,:); else try [temp, o,
it]=emd(medias(end,:),'MAXMODES',1,'MAXITERATIONS',MaxIter);
catch
temp=emd(medias(end,:),'MAXMODES',1,'MAXITERATIONS',MaxIter);
it=0; disp('catch 2 sin ruido') end;
temp=temp(end,:); end; aux=aux+temp/NR;
iter(i,k+1)=it;
end; modes=[modes;medias(end,:)-aux]; medias =
[medias;aux];
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aux=zeros(size(x)); k=k+1; es_imf =
min(size(emd(medias(end,:),'MAXMODES',1,'MAXITERATIONS',MaxIter)));end;modes
= [modes;medias(end,:)];modes=modes*desvio_x;its=iter;
