CEEMDAN-小波阈值联合去噪（软阈值）

%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 分解信号 %Nstd: noise standard deviation 噪声标准偏差 %NR: number of realizations 实现次数 %MaxIter: maximum number of sifting iterations allowed.允许的最大筛选迭代次数 %SNRFlag: if equals 1, then the SNR increases for every stage, as in[1]. 为1时，每个阶段的SNR都会增加 % If equals 2, then the SNR is the same for all stages, as in[2].为2时，则所有阶段的SNR都相同 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % The current is an improved version, introduced in: %[1] Colominas MA, Schlotthauer G, Torres ME. "Improve complete ensemble EMD: A suitable 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 Empirical 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: macolominas@bioingenieria.edu.ar %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)); 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 realizations end; for i=1:NR modes_white_noise{i}=emd(white_noise{i});%calculates the modes of white gaussian noise end; 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 mode medias = 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; 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; end; temp=temp(end,:); end; aux=aux+temp/NR; iter(i,k+1)=it; end; modes=[modes;medias(end,:)-aux]; medias = [medias;aux]; 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;