A GAN noise modeling based blind denoising method for guided waves

Intelligent identification technology for high‐order digital modulation signals under low signal‐to‐noise ratio conditions

“…To test the denoising performance of GANs, Cui et al. proposed a noise reduction network based on anti‐network and self‐encoder generation, which can effectively reduce the noise level, and the performance of noise reduction under low SNR conditions is significantly better than that of traditional denoising methods [20]. Ashraf et al.…”

“…To solve this problem, this paper uses a GAN-based method to improve the robustness of the denoising network [19]. To test the denoising performance of GANs, Cui et al proposed a noise reduction network based on anti-network and selfencoder generation, which can effectively reduce the noise level, and the performance of noise reduction under low SNR conditions is significantly better than that of traditional denoising methods [20]. Ashraf et al applied in the audio field to solve underwater acoustic noise removal by removing background environmental noise [21].…”