BCI_MI_CSP_DNN

Directory: matlab
Plat: matlab
Size: 14486KB
Downloads: 8
Upload time: 2019-09-27 19:53:26
Uploader: 渔舟唱晚1
Description:   In this study, our goal was to use deep learning methods to improve the classification performance of motor imagery EEG signals. Therefore, we propose a classification method based on deep learning for motor imagery EEG signals. Based on the pre-processed raw EEG signals, a co-space model (CSP) method is used to extract the EEG feature matrix, which is then fed to a deep neural network (DNN) for training and classification. Our work was tested experimentally on the BCI Competition II Dataset III dataset, and the best DNN framework was proposed, achieving an accuracy of 83.6%.

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