时序分解 | Matlab实现EEMD集合经验模态分解时间序列信号分解

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时序分解 | Matlab实现EEMD集合经验模态分解时间序列信号分解

效果一览

在这里插入图片描述

基本介绍

Matlab实现EEMD集合经验模态分解时间序列信号分解
1.分解效果图，效果如图所示，可完全满足您的需求～
2.直接替换数据即可用适合新手小白注释清晰～
3.附赠案例数据直接运行main一键出图～

程序设计

完整源码和数据获取方式：Matlab实现EEMD集合经验模态分解时间序列信号分解。

function [modos its]=eemd(x,Nstd,NR,MaxIter)
%--------------------------------------------------------------------------
%WARNING: this code needs to include in the same
%directoy the file emd.m developed by Rilling and Flandrin.
% -------------------------------------------------------------------------
%  OUTPUT
%   modos: contain the obtained modes in a matrix with the rows being the modes
%   its: contain the iterations needed for each mode for each realization
%
%  INPUT
%  x: signal to decompose
%  Nstd: noise standard deviation
%  NR: number of realizations
%  MaxIter: maximum number of sifting iterations allowed.
% -------------------------------------------------------------------------
%   Syntax
%
%   modos=eemd(x,Nstd,NR,MaxIter)
%  [modos its]=eemd(x,Nstd,NR,MaxIter)
% -------------------------------------------------------------------------
%  NOTE:   if Nstd=0 and NR=1, the EMD decomposition is obtained.
% -------------------------------------------------------------------------iter=it;
if NR>=2for i=2:NRxconruido=x+Nstd*randn(size(x));[temp, ort, it]=emd(xconruido,'MAXITERATIONS',MaxIter);temp=temp/NR;lit=length(it);[p liter]=size(iter);if lit<literit=[it zeros(1,liter-lit)];end;if liter<lititer=[iter zeros(p,lit-liter)];end;iter=[iter;it];[filas columnas]=size(temp);[alto ancho]=size(modos);diferencia=alto-filas;if filas>altomodos=[modos; zeros(abs(diferencia),ancho)];end;if alto>filastemp=[temp;zeros(abs(diferencia),ancho)];end;modos=modos+temp;end;