Adversarial denoising of EEG signals: a comparative analysis of standard GAN and WGAN-GP approaches

IntroductionElectroencephalography (EEG) signals frequently contain substantial noise and interference, which can obscure clinically and scientifically relevant features. Traditional denoising approaches, such as linear filtering or wavelet thresholding, often struggle with nonlinear or time-varying...

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Bibliografski detalji

Glavni autori:	Imad Eddine Tibermacine, Samuele Russo, Francesco Citeroni, Giuseppe Mancini, Abdelaziz Rabehi, Amal H. Alharbi, El-Sayed M. El-kenawy, Christian Napoli
Format:	Artigo
Jezik:	Inglês
Izdano:	Frontiers Media S.A. 2025-05-01
Serija:	Frontiers in Human Neuroscience
Teme:	EEG denoising generative adversarial network Wasserstein GAN brain-computer interface deep learning
Online pristup:	https://www.frontiersin.org/articles/10.3389/fnhum.2025.1583342/full
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