Electroencephalogram identity recognition method and system based on graph neural network
A technology of identity recognition and neural network, which is applied in the field of EEG identity recognition method and system based on graph neural network, can solve the problems of not using spatial features and topological relationships, classifier learning, etc., and achieve improved classification accuracy, good Interpretability, the effect of reducing overfitting problems
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[0031] like figure 1 As shown, the EEG identity authentication method based on the graph neural network in this embodiment includes:
[0032] 1) Collect the EEG signals when the user performs the identification operation;
[0033] 2) Extracting map feature data from the EEG signal;
[0034] 3) Input the graph feature data into the pre-trained graph neural network to obtain the identification result. Graph Neural Network (GCN) is also known as Graph Neural Network. Graph Neural Network is a generalization of Convolutional Neural Network in the graph domain. It can perform deep learning on graph data, and can perform end-to-end on the node information and structural information of the graph at the same time. Learning is currently the best choice for learning tasks on graph data. In this embodiment, the EEG data constitutes typical graph data. Applying the graph neural network to the classification learning of EEG data can take into account the spatial characteristics of each...
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