Auditory attention tracking states in a cocktail party environment can be decoded by deep convolutional neural networks

Volume: 17, Issue: 3, Pages: 036013 - 036013
Published: Jun 12, 2020
Abstract
Objective. A deep convolutional neural network (CNN) is a method for deep learning (DL). It has a powerful ability to automatically extract features and is widely used in classification tasks with scalp electroencephalogram (EEG) signals. However, the small number of samples and low signal-to-noise ratio involved in scalp EEG with low spatial resolution constitute a limitation that might restrict potential brain-computer interface (BCI)...
Paper Details
Title
Auditory attention tracking states in a cocktail party environment can be decoded by deep convolutional neural networks
Published Date
Jun 12, 2020
Volume
17
Issue
3
Pages
036013 - 036013
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