function imf = emd(x,n);%%最好把函数名改为emd1之类的，以免和Grilling的emd冲突
%%n为你想得到的IMF的个数
c = x('; % copy of the input signal (as a row vector)
N = length(x);-
% loop to decompose the input signal into n successive IMFs
imf = []; % Matrix which will contain the successive IMF, and the residuefor t=1:n
% loop on successive IMFs
%-------------------------------------------------------------------------
% inner loop to find each imf
h = c; % at the beginning of the sifting process, h is the signal
SD = 1; % Standard deviation which will be used to stop the sifting process
while SD > 0.3 % while the standard deviation is higher than 0.3 (typical value) %%筛选停止准则
% find local max/min points
d = diff(h); % approximate derivative %%求各点导数
maxmin = []; % to store the optima (min and max without distinction so far)
for i=1:N-2
if d(i)==0 % we are on a zero %%导数为0的点，即”
驻点“，但驻点不一定都是
极值点，如y=x^3的x=0处
if sign(d(i-1))~=sign(d(i+1)) % it is a maximum %%如果驻点两侧的导数异号（如一边正，一边负），那么该点为极值点
maxmin = [maxmin, i]; %%找到极值点在信号中的坐标（不分极大值和极小值点）
end
elseif sign(d(i))~=sign(d(i+1)) % we are straddling a zero so%%如y=|x|在x=0处是极值点，但该点倒数不存在，所以不能用上面的判
断方法
maxmin = [maxmin, i+1]; % define zero as at i+1 (not i) %%这里提供了另一类极值点的判断方法
end
end
if size(maxmin,2) < 2 % then it is the residue %%判断信号是不是已经符合残余分量定义
break
end
% divide maxmin into maxes and mins %% 分离极大值点和极小值点
if maxmin(1)>maxmin(2) % first one is a max not a min
maxes = maxmin(1:2:length(maxmin));
mins = maxmin(2:2:length(maxmin));
else % is the other way around
maxes = maxmin(2:2:length(maxmin));
mins = maxmin(1:2:length(maxmin));
end % make endpoints both maxes and mins
maxes = [1 maxes N];
mins = [1 mins N];
%------------------------------------------------------------------------- % spline interpolate to get max and min envelopes; form imf
maxenv = spline(maxes,h(maxes),1:N); %%用样条函数
插值拟合所有的极大值点
minenv = spline(mins, h(mins),1:N); %%用样条函数插值拟合所有的极小值点
m = (maxenv + minenv)/2; % mean of max and min enveloppes %%求上下
包络的均值
prevh = h; % copy of the previous value of h before modifying it %%h为分解前的信号
h = h - m; % substract mean to h %% 减去包络均值
% calculate standard deviation
eps = 0.0000001; % to avoid zero values
SD = sum ( ((prevh - h).^2) ./ (prevh.^2 + eps) ); %% 计算停止准则
end
imf = [imf; h]; % store the extracted IMF in the matrix imf
% if size(maxmin,2)<2, then h is the residue
% stop criterion of the algo. if we reach the end before n
if size(maxmin,2) < 2
break
end
c = c - h; % substract the extracted IMF from the signal
end
return
参考资料
http://zhidao.baidu.com/link?url=Dv2ef87TOGx8zcbCT1UJsZ2kutWrm4FuT5kbMZY5mAAn5yv7APibQ1y8fSag5JvbF2fKlI5jhgpTXu95SDRgi_