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Improved blind source separation method based on independent component analysis and empirical mode decomposition

机译:基于独立分量分析和经验模态分解的改进盲源分离方法

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Blind source separation (BSS) has recently received a great deal of attention in signal processing. In order to improve the limited separation performance of the conventional BSS method by the influence of the probability density of the source signal, based on the Independent Component Analysis and Empirical Mode Decomposition theories, an improved blind separation method is proposed. The method is demonstrated by some examples. Simulation results show the improved separation performance of the proposed method, and the time-frequency feature of the source signal has a better reflection.
机译:盲源分离(BSS)最近在信号处理中受到了广泛的关注。为了通过源信号概率密度的影响来提高常规BSS方法的有限分离性能,基于独立分量分析和经验模态分解理论,提出了一种改进的盲分离方法。通过一些示例说明了该方法。仿真结果表明,所提方法具有更好的分离性能,并且源信号的时频特性具有较好的反射效果。

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