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呵呵,可能大家都有了这个程序了,不过我觉得这个程序对我现在刚学EMD很有帮助,
因为程序简单,太长了初学的时候没有耐心看那么多行的程序
我根据我的理解对程序作了一些简单的注释,EMD原理基本理解,但是对于程序具体实现时有些地方不太懂,欢迎大家指正,共同探讨。
这个程序是一个最基本的程序,没有包括任何改进算法,如端点延拓等。
% EMD: Emprical mode decomposition
%
% imf = emd(x,n)
%
% x - input signal (must be a column vector)
% n - number of intrinsic mode functions
%
% imf - Matrix of intrinsic mode functions (each as a row)
%
% See: Huang et al, Royal Society Proceedings on Math, Physical,
% and Engineering Sciences, vol. 454, no. 1971, pp. 903-995,
% 8 March 1998
%
% Author: Ivan Magrin-Chagnolleau <ivan@ieee.org>
%
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
[ 本帖最后由 zhlong 于 2007-5-16 12:01 编辑 ] |