A spiking neural network with probability information transmission

摘要: Abstract The spiking neural network provides a potential computing paradigm for simulating the complex information processing mechanism of brain. Even though there are many theoretical and practical achievements, several crucial problems remain to be addressed existing learning algorithm. In this paper, Probabilistic Spike Response Model (PSRM), which ignition mode is determined neither by difference between threshold membrane voltage nor in form pulses, proposed from probabilistic perspective. PSRM reconstructs probability relationship neuron transmit probabilities redefines pulses. expression pulse sequence makes model continuous differentiable so as avoid difficulty using supervised algorithms. our study, single-layer algorithm multilayer based on also given. As shown experiments, method value.