Spiking neural network, which simulates neurons more closely to the actual situation, also takes into account the influence of time information. The idea is that neurons in a dynamic neural network are not activated in every iteration of propagation (as is the case in a typical multilayer perceptron network), but only when its membrane potential reaches a certain value. When a neuron is activated, it produces a signal that is passed on to other neurons, raising or lowering their membrane potential.