Deep Learning of EEG Time–Frequency Representations for Identifying Eye States

Volume: 10, Issue: 02, Pages: 1840006 - 1840006
Published: Apr 1, 2018
Abstract
A new Convolutional Neural Network (CNN) architecture to classify nonstationary biomedical signals using their time–frequency representations is proposed. The present method uses the spectrogram of the biomedical signals as an input to CNN, in addition Non-negative matrix factorization (NMF) dictionary elements are used as an additional feature to improve the performance of the CNN model. Considering a number of applications involving eye state...
Paper Details
Title
Deep Learning of EEG Time–Frequency Representations for Identifying Eye States
Published Date
Apr 1, 2018
Volume
10
Issue
02
Pages
1840006 - 1840006
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