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- Title
EEG Emotion Recognition Based on 3DC-BGRU.
- Authors
HU Zhangfang; LIU Pengfei; JIANG Qin; LUO Fei; WANG Mingli
- Abstract
To solve the problem of low emotional recognition rate of EEG signals, this paper proposes an EEG emotion recognition method based on 3DC-BGRU. Firstly, the Short-Time Fourier Transform(STFT) is performed on the singlechannel EEG signal, and the time-frequency information of the relevant frequency band is extracted to form a two-dimensional time-frequency map, the time-frequency map of multiple channels constitutes a new three-dimensional data form of time, frequency and channels. Then, a novel Convolutional Neural Network(CNN) model is designed to extract deep features of 3D data by 3D convolution. Finally, the Bidirectional Gated Recurrent Unit(BGRU) is designed to process the sequence information of deep features and classify them with Softmax. The experimental results show that the classification recognition rate of the method is improved.
- Publication
Journal of Computer Engineering & Applications, 2020, Vol 56, Issue 20, p111
- ISSN
1002-8331
- Publication type
Article
- DOI
10.3778/j.issn.1002-8331.1906-0395