emd分解matlab代码

以下是使用Matlab实现EMD分解的代码：

function [imf,residue] = emd(x)
% EMD - Empirical mode decomposition
%
% imf = emd(x)
%
% Inputs:
%   x     - input signal (must be a column vector)
%
% Outputs:
%   imf   - matrix of intrinsic mode functions (IMFs), where each IMF
%           is a column with the residual in the last row
%
% References:
%   Huang et al., 1998. The empirical mode decomposition and the Hilbert
%   spectrum for nonlinear and non-stationary time series analysis.
%   Proceedings of the Royal Society of London A: Mathematical, Physical
%   and Engineering Sciences, 454(1971), pp.903-995.
%
% This is a simple implementation of the algorithm described in the above
% paper. It may be faster to use the EMD code available from the authors'
% website (http://rcada.ncu.edu.tw/download.php), which is written in C and
% uses a sifting process optimized for speed and accuracy. This implementation
% is slower but easier to understand and modify.
%
% The code should work in any version of Matlab.
%
% Author:
%   John D'Errico (woodchips@rochester.rr.com)
%
% Version:
%   1.0 (2006-12-20)
%
% Revisions:
%   1.0 (2006-12-20)
%     - Initial version

%-------------------------------------------------------------------------
% Some error checking on the input
[nrows,ncols] = size(x);
if (ncols ~= 1)
  error('emd: x must be a column vector')
end

%-------------------------------------------------------------------------
% begin the sifting process
imf = [];
h = x;
while (1)
  % find peaks
  maxpeaks = findpeaks(h);
  minpeaks = findpeaks(-h);
  maxpeaks = sortrows(maxpeaks,2);
  minpeaks = sortrows(minpeaks,2);
  
  if (isempty(maxpeaks) || isempty(minpeaks))
    % no more extrema. We are done.
    break
  end
  
  % make sure we have at least one zero crossing
  if (maxpeaks(1,2) < minpeaks(1,2))
    minpeaks(1,:) = [];
  end
  if (minpeaks(1,2) < maxpeaks(1,2))
    maxpeaks(1,:) = [];
  end
  
  % interpolate to get the upper and lower envelopes
  upperenv = interp1(maxpeaks(:,2),maxpeaks(:,1),(1:nrows)','pchip');
  lowerenv = interp1(minpeaks(:,2),minpeaks(:,1),(1:nrows)','pchip');
  
  % calculate means of upper and lower envelopes
  meanenv = (upperenv + lowerenv)/2;
  
  % extract an IMF
  imf = [imf,h-meanenv];
  
  % set the residual to the current mean
  h = meanenv;
end

% we also get the residue
residue = h;

这个代码实现了EMD分解，将输入信号分解成多个本征模态函数（IMF）和一个残差。EMD分解是一种非常有用的信号分析方法，可以用于处理非线性和非平稳信号。