基于改进的EMD的数据包络分析
基于改进的EMD的数据包络分析：代码下载链接：https://pan.baidu.com/s/1WqcjVf2c50CYxy7-htP8ag
提取码：5ebi
function imf = emd2(x)
% Empiricial Mode Decomposition (Hilbert-Huang Transform)
% imf = emd(x)
% Func : findpeaks
x = transpose(x(:));% 转置
imf = [];
while ~ismonotonic(x) % 当x不是单调函数，分解终止条件
x1 = x;
sd = Inf; % 均值
% 直到x1满足IMF条件，得c1
while (sd > 0.1) || ~isimf(x1) % 当标准偏差系数sd大于0.1或x1不是固有模态函数时，分量终止条件
s1 = getspline2(x1); % 上包络线
s2 = -getspline2(-x1); % 下包络线
x2 = x1-(s1+s2)/2; % 此处的x2为文章中的h
sd = sum((x1-x2).^2)/sum(x1.^2);
x1 = x2;
end
imf= ;
x = x-x1;
end样条拟合改进如下：
function s = getspline2(x)
% 三次样条函数拟合成元数据包络线
N = length(x);
p = findpeaks(x);
% s = spline(,,1:N);
if(length(p)>2)
x1 = p(1);y1 = x(x1);
x2 = p(2);y2 = x(x2);
x3 = 0;y3 = (y2-y1)./(x2-x1+eps).*(x3-x1)+y1;
x4 = p(end); y4 = x(x4);
x5 = p(end-1);y5 = x(x5);
x6 = N+1;y6 = (y5-y4)./(x5-x4+eps).*(x6-x4)+y4;
s = spline(,,1:N);
else
s = spline(,,1:N);
end代码运行效果：
https://www.bilibili.com/video/BV1b341187EZ?spm_id_from=333.999.0.0
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