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首页> 外文期刊>Journal of information and computational science >A Single Channel EMI Signal Separation Method Based on Directly-mean Empirical Mode Decomposition
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A Single Channel EMI Signal Separation Method Based on Directly-mean Empirical Mode Decomposition

机译:基于直接均值经验模态分解的单通道EMI信号分离方法

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摘要

ICA is a powerful decomposition method for time-domain series, except for the requirement that the number of observed signals and the source signals should be the same, which makes ICA fail to process single channel signals. In this paper, we propose a new method using directly-mean EMD, which is utilized to extract independent components from a single channel mixture. The proposed method could overcome the side effect of original EMD, and can be applied to the separation of EMI signals to locate interference sources. Simulation experimental results demonstrate the effectiveness of the proposed method, and show that the proposed method outperforms the comparison methods, such as the original EMD ICA and wavelet ICA.
机译:ICA是时域序列的强大分解方法,除了要求观察信号和源信号的数量必须相同之外,这使得ICA无法处理单通道信号。在本文中,我们提出了一种使用直接均值EMD的新方法,该方法用于从单通道混合物中提取独立成分。所提出的方法可以克服原始EMD的副作用,可以应用于EMI信号的分离以定位干扰源。仿真实验结果证明了该方法的有效性,表明该方法优于原始的EMD ICA和小波ICA等比较方法。

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