提出了一种基于经验模式分解的气液两相流流型识别方法。
A method of flow regime identification based on empirical mode decomposition was proposed.
本文基于经验模式分解理论提出了一种新的分割方法。
This paper proposes a new image segmentation method based on the theory of EMD.
研究结果表明：基于经验模式分解的时频分析方法可以很有效地提取到非平稳故障特征信号，是一种适合于非线性信号处理的方法。
The experiment result shows that the time-frequency method based on EMD can effectively extract the feature of unbalanced fault signal and is proper for non-frequency modulation signal procession.
提出一种基于二维经验模式分解(BEMD)的图像水印嵌入算法，完成水印的嵌入和提取。
This paper proposes an image processing method which is based on Bidimensional Empirical Mode Decomposition (BEMD). BEMD is applied in watermark embedding and extraction.
为了避免经验模式分解(EMD)过程中不同时间尺度函数间的模式混叠，采用基于高斯白噪声加入的经验模式分解方法，并将之应用于旋转机械故障诊断中。
The EMD added Gauss white noise is proposed to avoid mode mixing of different time-scale IMF, and is applied in fault diagnosis for rotating machine.
本论文研究了以图像为载体，基于经验模式分解算法的信息隐藏。
This thesis researches on the hiding information which held the image as the carrier and based on empirical mode decomposition algorithm.
研究了强噪声混合条件下微弱信号的经验模式分解（EMD）问题，提出了一种基于随机共振降噪的EMD分解方法。
To deal with this problem, comparison is made between the empirical mode decomposition(EMD) and the wavelet method in terms of signal trend extraction.
研究了强噪声混合条件下微弱信号的经验模式分解（EMD）问题，提出了一种基于随机共振降噪的EMD分解方法。
To deal with this problem, comparison is made between the empirical mode decomposition(EMD) and the wavelet method in terms of signal trend extraction.
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