function [imf,ort,nbits] = emd_local(x,t,stop,tst);% EMD_LOCAL ("Local" Empirical Mode Decomposition) computes a% local version of EMD%% stopping criterion for sifting : %   at each point : mean amplitude < threshold2*envelope amplitude%   &%   mean of boolean array ((mean amplitude)/(envelope amplitude) > threshold) < tolerance%   &%   |#zeros-#extrema|<=1%%% [imf,ort,nbits] = EMD_LOCAL(x,t,stop,tst)% inputs: %         - x : analyzed signal (line vector)%         - t (optional) : sampling times (line vector) (default : 1:length(x))%         - stop (optional) : threshold, threshold2 and tolerance (optional)%                             for sifting stopping criterion %                             default : [0.05,0.5,0.05]%         - tst (optional) : if equals to 1 shows sifting steps with pause%                            if equals to 2 no pause%% outputs:%         - imf : intrinsic mode functions (last line = residual)%         - ort : index of orthogonality%         - nbits : number of iterations for each mode%% calls:%         - extr (finds extrema and zero-crossings)%         - io : computes the index of orthogonality% % G. Rilling, July 2002defstop = [0.05,0.5,0.05];if(nargin==1)  t = 1:length(x);  stop = defstop;  tst = 0;endif(nargin==2)  stop = defstop;  tst = 0;endif (nargin==3)  tst=0;endS = size(x);if ((S(1) > 1) & (S(2) > 1)) | (length(S) > 2)  error('x must have only one row or one column')endif S(1) > 1  x = x';endS = size(t);if ((S(1) > 1) & (S(2) > 1)) | (length(S) > 2)  error('t must have only one row or one column')endif S(1) > 1  t = t';endif (length(t)~=length(x))  error('x and t must have the same length')endS = size(stop);if ((S(1) > 1) & (S(2) > 1)) | (S(1) > 3) | (S(2) > 3) | (length(S) > 2)  error('stop must have only one row or one column of max three elements')endif S(1) > 1  stop = stop';  S = size(stop);endif S(2) <2  stop(2)=defstop(2);endif S(2) < 3  stop(3)=defstop(3);endsd = stop(1);sd2 = stop(2);tol = stop(3);%if tst % figure % end% maximum number of iterationsMAXITERATIONS=2000;% minimum length of the constant part of curve appended to zones badsx==1LARGMIN = 5;% maximum number of points symmmetrized for interpolationsNBSYM = 5;lx = length(x);sdt(lx) = 0;sdt = sdt+sd;sd2t(lx) = 0;sd2t = sd2t+sd2;% number of extrema and zero-crossings in residualner = lx;nzr = lx;r = x;imf = [];k = 1;% iterations counter for the extraction of 1 modenbit=0;% total iterations counterNbIt=0;% loop start : modes extracted while at least 3 extremawhile ner > 2    figure          % current mode  m = r;    % mode at previous iteration  mp = m;  sx = sd + 1;  badsx = 1;  % tests if enough extrema to proceed  test = 0;    [indmin,indmax,indzer] = extr(m);  lm=length(indmin);  lM=length(indmax);  nem=lm + lM;  nzm=length(indzer);    j=1;    % sifting loop  while (mean(badsx) > tol | (abs(nzm-nem)>1))&(test == 0)&nbit<MAXITERATIONS        if(nbit>MAXITERATIONS/5 & mod(nbit,floor(MAXITERATIONS/10))==0)      disp(['mode ',int2str(k),' nombre d iterations : ',int2str(nbit)])      disp(['stop parameter mean value : ',num2str(s)])   end    % boundary conditions for interpolations :        if indmax(1) < indmin(1)      if m(1) > m(indmin(1))        lmax = fliplr(indmax(2:min(end,NBSYM+1)));        lmin = fliplr(indmin(1:min(end,NBSYM)));        lsym = indmax(1);      else        lmax = fliplr(indmax(1:min(end,NBSYM)));        lmin = [fliplr(indmin(1:min(end,NBSYM-1))),1];        lsym = 1;      end    else      if m(1) < m(indmax(1))        lmax = fliplr(indmax(1:min(end,NBSYM)));        lmin = fliplr(indmin(2:min(end,NBSYM+1)));        lsym = indmin(1);      else        lmax = [fliplr(indmax(1:min(end,NBSYM-1))),1];        lmin = fliplr(indmin(1:min(end,NBSYM)));        lsym = 1;      end    end        if indmax(end) < indmin(end)      if m(end) < m(indmax(end))        rmax = fliplr(indmax(max(end-NBSYM+1,1):end));        rmin = fliplr(indmin(max(end-NBSYM,1):end-1));        rsym = indmin(end);      else        rmax = [lx,fliplr(indmax(max(end-NBSYM+2,1):end))];        rmin = fliplr(indmin(max(end-NBSYM+1,1):end));        rsym = lx;      end    else      if m(end) > m(indmin(end))        rmax = fliplr(indmax(max(end-NBSYM,1):end-1));        rmin = fliplr(indmin(max(end-NBSYM+1,1):end));        rsym = indmax(end);      else        rmax = fliplr(indmax(max(end-NBSYM+1,1):end));        rmin = [lx,fliplr(indmin(max(end-NBSYM+2,1):end))];        rsym = lx;      end    end        tlmin = 2*t(lsym)-t(lmin);    tlmax = 2*t(lsym)-t(lmax);    trmin = 2*t(rsym)-t(rmin);    trmax = 2*t(rsym)-t(rmax);        % in case symmetrized parts do not extend enough    if tlmin(1) > t(1) | tlmax(1) > t(1)      if lsym == indmax(1)        lmax = fliplr(indmax(1:min(end,NBSYM)));      else        lmin = fliplr(indmin(1:min(end,NBSYM)));      end      if lsym == 1        error('bug')      end      lsym = 1;      tlmin = 2*t(lsym)-t(lmin);      tlmax = 2*t(lsym)-t(lmax);    end            if trmin(end) < t(lx) | trmax(end) < t(lx)      if rsym == indmax(end)        rmax = fliplr(indmax(max(end-NBSYM+1,1):end));      else        rmin = fliplr(indmin(max(end-NBSYM+1,1):end));      end      if rsym == lx        error('bug')      end      rsym = lx;      trmin = 2*t(rsym)-t(rmin);      trmax = 2*t(rsym)-t(rmax);    end                  mlmax =m(lmax);     mlmin =m(lmin);    mrmax =m(rmax);     mrmin =m(rmin);        % definition of enveloppes from interpolation            envmax = interp1([tlmax t(indmax) trmax],[mlmax m(indmax) mrmax],t,'spline');    envmin = interp1([tlmin t(indmin) trmin],[mlmin m(indmin) mrmin],t,'spline');        envmoy = (envmax + envmin)/2;    % estimation of mode amplitude        amp = abs(envmax-envmin)/2;    if any(amp == 0)      amp = amp+1e-300;   % circumvents divide by zero    end    mamp = max(amp);    sx=(abs(envmoy))./amp;    s = mean(sx);        % definition of f equal to 1 where sifting is needed and     % dcays fast to 0 in the neighbourhood    badsx = (sx > sd & amp > mamp/20) | (sx > sd2 & amp > mamp/100);    d = diff([0 badsx 0]);    debs = find(d==1);    fins = find(d==-1)-1;    if length(debs)~=length(fins)      error('pb avec le regroupement en composantes connexes')    end    indextr = sort([indmin indmax]);    d = diff(indextr);    f = [];    connexe = [];    lc = length(debs);    if lc > 0      connexe(lc,lx) = 0;      for i = 1:lc        connexe(i,debs(i):fins(i)) = 1;    % indices of previous and next extrema    indp = min([nem-1,length(find(indextr < debs(i)))]);        inds = max([2,length(find(indextr <= fins(i)))+1]);		    % evaluation of extrema densities left and right        llarg = mean(d(min([nem-1,max([1,indp])]):max([1,min([nem-1,indp + 2])])));        rlarg = mean(d(min([nem-1,max([1,inds - 1])]):max([1,min([nem-1,inds + 1])])));    larg = mean([rlarg,llarg]);	    % special cases...    if indp == 0          if inds ~= (nem+1)            larg = (indextr(inds)-indextr(inds-1));          else            larg = round(lx/2);          end        else          if  inds ~= (nem+1)            larg = max([(indextr(inds)-indextr(inds-1)),(indextr(indp+1)-indextr(indp))]);          else            larg =(indextr(indp+1)-indextr(indp));          end        end        larg = 2*max([round((fins(i)-debs(i))/4),larg,LARGMIN]);    w(1:round(larg/2)) = [1:round(larg/2)]/round(larg/2);        w((2*larg+2-round(larg/2)):(2*larg+1)) = fliplr(w(1:round(larg/2)));        w(round(larg/2):(2*larg+2-round(larg/2))) = 1;        indd = max(1,debs(i)-larg);        indf = min(lx,fins(i)+larg);        connexe(i,indd:debs(i)) = w((larg+1-debs(i)+indd):(larg+1));        connexe(i,fins(i):indf) = w((larg+1):(larg+1+indf-fins(i)));      end      f = max(connexe,[],1);        else      f(lx) = 0;    end        m = m - f.*envmoy;        [indmin,indmax,indzer] = extr(m);    lm=length(indmin);    lM=length(indmax);    nem = lm + lM;    nzm = length(indzer);        % display         if tst      subplot(5,1,1)      plot(t,mp);hold on;      plot(t,envmax,'--k');plot(t,envmin,'--k');plot(t,envmoy,'r');      title(['IMF ',int2str(k),';   iteration ',int2str(nbit),' before sifting']);      set(gca,'XTick',[])      hold  off      subplot(5,1,2)      plot(t,sx)      hold on      plot(t,sdt,'--r')      plot(t,sd2t,':k')      title('stop parameter')      set(gca,'XTick',[])      hold off      subplot(5,1,3)      plot(f)      title('mean ponderation')      set(gca,'XTick',[])            subplot(5,1,4)      plot(t,m)      title(['IMF ',int2str(k),';   iteration ',int2str(nbit),' after sifting']);      set(gca,'XTick',[])      subplot(5,1,5);      plot(t,r-m)      title('residue');      disp(['stop parameter mean value : ',num2str(s)])      if tst == 2        pause(0.01)      else        pause      end    end            % end loop :        if nem < 3      test = 1;    end                mp = m;    nbit=nbit+1;    NbIt=NbIt+1;    if(nbit==(MAXITERATIONS-1))      warning(['forced stop of sifting : too many iterations... mode ',int2str(k),'. stop parameter mean value : ',num2str(s)])    end    end  imf(k,:) = m;  nbits(k) = nbit;  k = k+1;  r = r - m;  [indmin,indmax,indzer] = extr(r);  ner = length(indmin) + length(indmax);  nzr = length(indzer);  nbit=1;    if (max(r) - min(r)) < (1e-10)*(max(x) - min(x))    if ner > 2      warning('forced stop of EMD : too small amplitude')    else      disp('forced stop of EMD : too small amplitude')    end    break  end  endimf(k,:) = r;ort = io(x,imf);if tst  closeend