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With the promotion of brain-computer interface technology, it is possible to study brain control system through EEG signals in recent years. In order to solve the problem of EEG signal classification effectively, a motor imagery classification algorithm based on recurrence plot convolution neural network is proposed. Firstly, EEG signals are preprocessed to enhance the signal intensity in the exercise interval. Secondly, time-domain and frequency-domain features are extracted respectively to construct the feature mode of recurrence plot. Finally, a new neural network is established to realize the accurate recognition of left and right movements. This research can also be transferred to other research fields.
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