Matlab 互补集合经验模态分解(CEEMD)的信号分解（Matlab完整源码和数据）

% Y: Inputted data; % Nstd: ratio of the standard deviation of the added noise and that of Y; % NE: Ensemble member being used % TNM: total number of modes (not including the trend) % function allmode=ceemd(Y,Nstd,NE,TNM) % find data length xsize=length(Y); dd=1:1:xsize; % Nornaliz data Ystd=std(Y); Y=Y/Ystd; % Initialize saved data 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 % adding noise for i=1:xsize, temp=randn(1,1)*Nstd; X1(i)=Y(i)+temp; X2(i)=Y(i)-temp; end % sifting X1 xorigin = X1; xend = xorigin; % save the initial data into the first column for jj=1:1:xsize mode(jj,1) = xorigin(jj); end nmode = 1; while nmode <= TNM, xstart = xend; iter = 1; while iter<=5, [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; % save a mode for jj=1:1:xsize, mode(jj,nmode) = xstart(jj); end end % save the trend for jj=1:1:xsize, mode(jj,nmode+1)=xend(jj); end % add mode to the sum of modes from earlier ensemble members allmode=allmode+mode; %%%============================================================= % sifting X2 xorigin = X2; xend = xorigin; % save the initial data into the first column for jj=1:1:xsize, mode(jj,1) = xorigin(jj); end nmode = 1; while nmode <= TNM, xstart = xend; iter = 1; while iter<=5, [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; % save a mode for jj=1:1:xsize, mode(jj,nmode) = xstart(jj); end end % save the trend for jj=1:1:xsize, mode(jj,nmode+1)=xend(jj); end % add mode to the sum of modes from earlier ensemble members allmode=allmode+mode; %fprintf('-'); end % ensemble average allmode=allmode/NE/2; % Rescale mode to origional unit. allmode=allmode*Ystd;