The invention discloses a
convolutional neural network training method, an electroencephalogram
signal recognition method and device and a medium, and the method comprises the steps: executing a plurality of obtaining processes, obtaining an electroencephalogram
signal in each obtaining process, and executing the
time domain data enhancement and
frequency domain data enhancement of the electroencephalogram
signal, and training a
convolutional neural network by using the enhanced electroencephalogram signal, and the like. The
convolutional neural network trained by the method is a multi-input,multi-
convolution-scale and multi-
convolution-type
hybrid convolutional neural network, the sizes of a multi-input
convolution layer and a convolution kernel are reasonably designed, and the method has high recognition accuracy; a
training set used for training the convolutional neural network is obtained by performing
time domain data enhancement and
frequency domain data enhancement expansion based on the acquired electroencephalogram signals, so the training data volume of the convolutional neural network can be increased, the over-fitting phenomenon can be reduced,
noise interference in the electroencephalogram signals can be effectively coped with, and the recognition effect can be improved. The method is widely applied to the technical field of
signal processing.