经验模态分解matlab代码

以下是MATLAB中的经验模态分解（EMD）代码：

function [IMF,residual] = emd(x)
% x: input signal
% IMF: matrix of intrinsic mode functions
% residual: residual signal

% Set stopping criterion
sifting_stop = 0.1;

% Initialize variables
h = x;
IMF = [];
t = 0;
while true
    % Count iterations
    t = t + 1;
    
    % Extract extrema
    ext_max = islocalmax(h);
    ext_min = islocalmin(h);
    
    % Check if extrema exist
    if sum(ext_max) < 2 || sum(ext_min) < 2
        residual = h;
        break;
    end
    
    % Calculate upper and lower envelopes
    max_env = interp1(find(ext_max), h(ext_max), (1:numel(h))', 'pchip');
    min_env = interp1(find(ext_min), h(ext_min), (1:numel(h))', 'pchip');
    
    % Calculate mean envelope
    mean_env = (max_env + min_env) / 2;
    
    % Calculate difference between signal and mean envelope
    h_diff = h - mean_env;
    
    % Check if stopping criterion is met
    if sum(abs(h_diff)) < sifting_stop
        IMF = [IMF, h];
        residual = h_diff;
        break;
    end
    
    % Extract IMF
    h = h_diff;
    IMF = [IMF, h];
end
end

这个代码实现了EMD算法，将信号分解为一系列单调的本征模态函数（IMF），每个IMF都有相应的频率。IMF是通过不断提取信号的局部极值来获得的，然后计算出局部上限和下限，并使用均值作为该模态函数的IMF。这个过程一直持续到不再有任何IMF，最终剩余的信号被认为是残差信号。