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经验模式分解(Empirical Mode Decomposition,EMD)
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2015-11-01
15:26:34
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经验模式分解(Empirical Mode Decomposition,EMD)是一种新的信号处理技术,它是基于数据本身的,且能在空间域中将信号进行分解,从而可以区分噪声和有用信号。
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% This is an EMD/EEMD program
%
% function allmode=eemd(Y,Nstd,NE)
%
% INPUT:
% Y: Inputted data;
% Nstd: ratio of the standard deviation of the added noise and that
% of Y;(加性噪声的标准差与Y的比)
% NE: Ensemble number for the EEMD
% OUTPUT:
% A matrix of N*(m+1) matrix, where N is the length of the input
% data Y, and m=fix(log2(N))-1. Column 1 is the original data, columns 2, 3, ...
% m are the IMFs from high to low frequency, and comlumn (m+1) is the
% residual (over all trend).
%
% NOTE:
% It should be noted that when Nstd is set to zero and NE is set to 1, the
% program degenerates to a EMD program.(如果Nstd=0,NE=1,该函数退化成普通的EMD函数)
%
% References can be found in the "Reference" section.
%
% The code is prepared by Zhaohua Wu. For questions, please read the "Q&A" section or
% contact
% zhwu@cola.iges.org
%
function allmode=eemd(Y,Nstd,NE)
xsize=length(Y);
dd=1:1:xsize;
Ystd=std(Y); %计算Y的标准差
%
% function allmode=eemd(Y,Nstd,NE)
%
% INPUT:
% Y: Inputted data;
% Nstd: ratio of the standard deviation of the added noise and that
% of Y;(加性噪声的标准差与Y的比)
% NE: Ensemble number for the EEMD
% OUTPUT:
% A matrix of N*(m+1) matrix, where N is the length of the input
% data Y, and m=fix(log2(N))-1. Column 1 is the original data, columns 2, 3, ...
% m are the IMFs from high to low frequency, and comlumn (m+1) is the
% residual (over all trend).
%
% NOTE:
% It should be noted that when Nstd is set to zero and NE is set to 1, the
% program degenerates to a EMD program.(如果Nstd=0,NE=1,该函数退化成普通的EMD函数)
%
% References can be found in the "Reference" section.
%
% The code is prepared by Zhaohua Wu. For questions, please read the "Q&A" section or
% contact
% zhwu@cola.iges.org
%
function allmode=eemd(Y,Nstd,NE)
xsize=length(Y);
dd=1:1:xsize;
Ystd=std(Y); %计算Y的标准差
资源评论
- qq2298734662017-06-15原来是matlab代码来的~~~
qq_32475829
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