In the second stage, the spectral entropy values of the EEG indicators of all channels were calculated and these values were classified by the bidirectional long-short time period reminiscence structure in the third stage. In the final stage, the performance of the deep-learning architecture was evaluated with accuracy, sensitivity, specificity and receiver working attribute curve. With the proposed technique, an accuracy of seventy six.91% and a ROC value of 90% were obtained. Over 30 years we’ve been co-creating the electronic parts market.
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