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Neural Processing Letters

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20-09-2021

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

Authors: Hongyi Li, Wei Lin, Di Zhao

Published in: Neural Processing Letters | Issue 6/2021

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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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Title: BSS Method Based on Wavelet Transform and Improved EASI Algorithm and Its Application in EMI
Authors: Hongyi Li
Wei Lin
Di Zhao
Publication date: 20-09-2021
Publisher: Springer US
Published in: Neural Processing Letters / Issue 6/2021
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-021-10621-8

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