Jul 4, 2015 · Artificial neural networks (ANNs) are effective and powerful tools for removing interference from EEGs. Several methods have been developed, but ...
Noise removal in electroencephalogram signals using an artificial neural network based on the simultaneous perturbation method ... To read the full-text of this ...
Oct 1, 2016 · Artificial neural networks (ANNs) are effective and powerful tools for removing interference from EEGs. Several methods have been developed, but ...
Noise removal in electroencephalogram signals using an artificial ...
www.semanticscholar.org › paper
A new method of reducing all EEG interference signals in one step with low EEG distortion and high noise reduction is introduced, based on a growing ANN ...
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Auto-Denoising for EEG Signals Using Generative Adversarial Network
www.ncbi.nlm.nih.gov › PMC8914841
Feb 23, 2022 · In this paper, a generative adversarial network (GAN)-based denoising method is proposed to denoise the multichannel EEG signal automatically. A ...
Abstract: Electroencephalogram (EEG) recordings often experience interference by different kinds of noise, including white and muscle, severely limiting its ...
The system has been evaluated within a wide range of EEG signals. The present study introduces a new method of reducing all EEG interference signals in one step ...
Apr 25, 2024 · Noise removal in electroencephalogram signals using an artificial neural network based on the simultaneous perturbation method. Neural Comput.
The system was evaluated within a wide range of EEG signals in which noise was added. The present study introduces a method of reducing all EEG interference ...
A method of reducing all EEG interference signals with low EEG distortion and high noise reduction is introduced, based on a growing ANN that optimised the ...