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BSS Method Based on Wavelet Transform and Improved EASI Algorithm and Its Application in EMI

机译:基于小波变换的BSS方法及改进的EASI算法及其在EMI中的应用

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In recent years, the number of electrical and electronic devices used in production and life has been increasing. It leads to serious interference and aliasing among electromagnetic signals. To address electromagnetic interference (EMI) issues, we propose a feasible blind source separation method based on wavelet transform and improved equivariant adaptive separation via independence (EASI) algorithm. First, we leverage the wavelet transform algorithm to denoise mixed electromagnetic signals. Second, we use the variable step-size EASI algorithm to separate each signal from the mixed signals. It is inspired by the simulated annealing strategy. We conduct a series of experiments to demonstrate the effectiveness of WE method. The experimental results show that WE method can provide support for solving EMI problems.
机译:近年来,生产和生活中使用的电气和电子设备的数量一直在增加。 它导致电磁信号之间的严重干扰和混叠。 为了解决电磁干扰(EMI)问题,我们提出了一种基于小波变换的可行的盲源分离方法,通过独立(EASI)算法改进了等分性自适应分离。 首先,我们利用小波变换算法来代替混合电磁信号。 其次,我们使用可变步长easi算法将每个信号与混合信号分开。 它受到模拟退火策略的启发。 我们进行一系列实验来证明我们方法的有效性。 实验结果表明,我们的方法可以为解决EMI问题提供支持。

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