The invention relates to the field of neural network technology, and particularly to a parameter quantization method of a spiking neural network (SNN). According to the method of the invention, the original spiking neural network of which training is completed is obtained through offline mapping or online training, parameters of weights, thresholds, leakage constants, set voltage, refractory periods, synaptic delay and the like of the spiking neural network of which training is completed are quantified, and all layers of the neural network can share the same set of quantified parameters or each layer respectively has one set of quantified parameters. The spiking neural network after parameter quantization requires only a small number of parameters for realizing high-precision spiking-neural-network functions. According to the method, parameter storage space of the spiking neural network is effectively saved while high precision is maintained, operation speed is improved, and operationpower consumption is lowered.