The use of empirical mode decomposition (EMD) method and wavelet analysis in combination is explored for the detection of changes in the structural response data from structural damage diagnosis.
采用经验模式分解(EMD)与小波分析相结合的方法探讨结构响应数据信号，进行建筑结构损伤检测诊断。
Empirical mode decomposition(EMD) is a signal processing technique to decompose data set into several intrinsic mode functions(IMF) by a sifting process.
经验模式分解（EMD）通过筛分过程将原始信号分解成若干个基本模式分量（IMF），可看作无需预设带宽的自适应高通滤波方法。
A new scheme named Many-knot Empirical Mode decomposition (MEMD) of data decomposition for non-stationary data analysis is presented in this paper.
依据多结点样条函数插值理论，定义了模式函数，给出了数据分解过程。
In order to improve the forecast precision, a forecasting method based on empirical mode decomposition (EMD) and data mining method is proposed.
为了提高风电场风速短期预测的精度，提出了将经验模式分解与数据挖掘方法相结合对风速时间序列进行建模预测。
A prediction method based on support vector empirical mode decomposition (SVEMD) is proposed to deal with the non-linearity and non-stationarity of failure rate data.
针对故障率时间序列的非线性与非平稳特性，提出一种基于支持向量经验模态分解(SVEMD)的预测方法。
A prediction method based on support vector empirical mode decomposition (SVEMD) is proposed to deal with the non-linearity and non-stationarity of failure rate data.
针对故障率时间序列的非线性与非平稳特性，提出一种基于支持向量经验模态分解(SVEMD)的预测方法。
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