Electromagnetic Signal Denoising Method based on Improved Wavelet Threshold
Linlin Li, Zhengmei Zhang, Ye Liu, Anhui Feng · 2024
To solve the distortion problem of the existing wavelet threshold denoising algorithm when processing electromagnetic signals, an SSA combined with an improved threshold function wavelet denoising algorithm is given. The improved wavelet threshold function has high-order derivability characteristics, which can overcome the problems of hard and soft threshold functions, and the SSA algorithm enhances the adaptivity of the wavelet denoising algorithm to different noises. The algorithm of this paper is applied to simulation experiments and electromagnetic compatibility measured data. The denoising algorithm in this paper improves the SNR by 54.81% and 17.85%, and reduces the RMSE by 54.57% and 29.06%, respectively, compared with the traditional hard and soft threshold denoising algorithms. The results show that the denoising effect is better than the existing wavelet threshold denoising algorithm.