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

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Abstract

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.

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source signals

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source signal waveforms

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source signal (blue) waveforms

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source signal (blue) waveforms

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Acknowledgements

The project was supported by the National Natural Science Foundation of China (Grant No. 61771001).

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Authors and Affiliations

  1. LMIB, School of Mathematical Sciences, Beihang University, Beijing, 100191, China

    Hongyi Li & Di Zhao

  2. Key Laboratory of High Confidence Software Technologies, Peking University, Beijing, 100871, China

    Wei Lin

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  1. Hongyi Li
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  2. Wei Lin
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  3. Di Zhao
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Correspondence to Di Zhao.

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Most of Wei Lin’s work was done when he was at Beihang University.

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Li, H., Lin, W. & Zhao, D. BSS Method Based on Wavelet Transform and Improved EASI Algorithm and Its Application in EMI. Neural Process Lett 53, 4437–4449 (2021). https://doi.org/10.1007/s11063-021-10621-8

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