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EEMD-wp

于 2021-02-28 发布
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代码说明:

说明:  传统经验模态分解基于信号的极值点,例如δ(t) 函数就不能用 EMD 来处理,为抑制这一影响,Huang 于 2005 年提出了一种加噪的经验模态分解方法,即集总经验模态分解(Ensemble empirical mode decomposition,EEMD)。其基本原理是在原始信号上加上幅值很小的白噪声,然后做EMD分解,使不同尺度的信号成分映射到相应阶数的IMF 上。(Traditional empirical mode decomposition (EMD) is based on the extremum of signal)

文件列表:

EEMD-wp, 0 , 2020-12-06
EEMD-wp\kEEMD.m, 1256 , 2020-12-06
EEMD-wp\pEEMD.p, 408 , 2020-12-06
EEMD-wp\pEEMDandFFT.p, 529 , 2020-12-06
EEMD-wp\pFFT.p, 274 , 2020-12-06
EEMD-wp\testEEMD.m, 1789 , 2020-12-06
EEMD-wp\代码说明.docx, 285044 , 2020-12-06

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