An electroencephalogram signal classifying method and apparatus, an electroencephalogram signal classifying model training method and apparatus, and a medium, relating to the field of transfer learning. The method comprises: obtaining an electroencephalogram signal (201); performing feature extraction on the electroencephalogram signal to obtain a signal feature corresponding to the electroencephalogram signal (202); obtaining a differential distribution ratio for representing an effect of different types of differential distributions on the distribution of the signal feature and a source domain feature on a feature domain, the source domain feature being a feature corresponding to a source domain electroencephalogram signal (203); aligning the signal feature with the source domain feature according to the differential distribution ratio, to obtain an aligned signal feature (204); and classifying the aligned signal feature to obtain a motor imagery type corresponding to the electroencephalogram signal (205). By dynamically adjusting, by means of a differential distribution ratio, the distribution of a signal feature corresponding to an electroencephalogram signal on a feature domain, an electroencephalogram signal classifying model can recognize multiple types of electroencephalogram signals on the basis of the idea of transfer learning.
ELECTROENCEPHALOGRAM SIGNAL CLASSIFYING METHOD AND APPARATUS, ELECTROENCEPHALOGRAM SIGNAL CLASSIFYING MODEL TRAINING METHOD AND APPARATUS, AND MEDIUM