跪求一个emd 去噪的程序 matlab 代码 带中文解释的 方便理解

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 > 03 % while the standard deviation is higher than 03 (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 = 00000001; % 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

>

MakeONFilter， NormNoise2 MultiVisu2 MultiSURE2 这四个都是自己变得程序。你能找得到么，建议搜索 MakeONFilterm， NormNoise2m MultiVisu2m MultiSURE2m

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