关键词: 脉冲神经元, 敏感性, 突触, 扰动

Abstract: Spiking network is a kind of neural network model based on biological neuronal behavior. Its input and output are firing times of spikes and its working mechanism is more like the biological neural network. Information transfer between spiking neurons is encoded in the timing of individual spike times and due to this temporal coding its learning performance is better. The time characteristic of spiking neuron leads to its complex working mechanism, while the sensitivity of spiking neuron which reflects the perturbation of output caused by input perturbation can be used as a tool of researching on inner working mechanism of spiking neuron. Unlike the traditional neural network, the definition of sensitivity of spiking neuron is the ratio of the number of changed output spike times to the running time of the neuron and it can reflect directly the influence of input perturbation. The analysis of the sensitivity caused by different input perturbation shows the sensitivity of spiking neuron is complicated. The sensitivity is a constant when all the synapses are perturbed equally and different perturbed synapses will cause different sensitivity.

Key words: spiking neuron, sensitivity, synapse, perturbation