The invention discloses a fast classification method of EEG signals based on FPGA, a realization method and a device thereof. The hard logic of a CNN
network structure model suitable for the classification of EEG signals is constructed on FPGA, and the
convolution operation is converted into
matrix multiplication. The IP cores of each layer in the CNN
network structure model are established, and the IP cores of each layer in the CNN
network structure model are connected by using the
synchronous data flow method, and AXI4-Streaming register
chip is inserted between the adjacent IP cores; the EEG training data is received, the floating-
point data is converted to a fixed-point number with a preset number of bits, training the CNN network structure model, adjusting the CNN network structure model
weight value until the highest classification accuracy model is obtained, and the trained
model parameters are stored in DDR memory, so as to obtain FPGA which can realize the fast classificationof EEG signals, and the fast classification of EEG signals is carried out by using the CNN network structure model.