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📋📋📋本文目录如下：🎁🎁🎁

目录

💥1 概述

📚2 运行结果

🎉3 参考文献

🌈4 Matlab代码实现

RLMD 是一种改进的局部均值分解，由一组优化策略提供支持。优化策略可以处理LMD中的边界条件、包络估计和筛选停止准则。它同时从混合信号中提取一组单分量信号（称为乘积函数）及其相关的解调信号（即AM信号和FM信号），与其他自适应信号处理方法（如EMD）相比，这是最吸引人的特征。RLMD可用于时频分析。

部分代码：

[x, display, stop_thre, sifting_stopping_mode, max_iter, max_pfs, smooth_mode,...     ma_span, ma_iter_mode, extd_r, x_energy, pfs, ams, fms, iterNum, fvs]...     = initial(x,varargin{:});

% Initialize main loop i = 0; xs = x; % copy x to xs for sifting process, reserve original input as x. nx = length(x);

while i < max_pfs && ~stoplmd(xs, x_energy) % outer loop for PF selection         i = i+1;         % initialize variables used in PF sifting loop     a_i = ones(1,nx);     s_j = zeros(max_iter,nx);     a_ij = zeros(max_iter, nx);          % PF sifting iteration loop     j = 0;     stop_sifting = 0;     s = xs;          while j < max_iter && ~stop_sifting %  inner loop for sifting process                  j = j+1;         [m_j, a_j, n_extr] = lmd_mean_amp(s, smooth_mode, ma_span, ma_iter_mode,...             extd_r);         % force to stop iter if number of extrema of s is smaller than 3.         if n_extr < 3             break;         end         h_j = s-m_j; % remove mean.         s = h_j./a_j; % demodulate amplitude.         a_i = a_i .* a_j; % mulitiply every ai         a_ij(j, :) = a_i;         s_j(j, :) = s;         [stop_sifting,fvs(i,:)] = is_sifting_stopping(a_j, j, fvs(i,:), sifting_stopping_mode, stop_thre);              end % sift iteration loop          switch sifting_stopping_mode         case {'liu'}             [~, opt0] = min(fvs(i,1:j)); % ***Critical Step***             opt_IterNum = min(j, opt0); % in case iteration stop for n_extr