论文标题
尖峰神经元亚稳态系统的时间平均值的收敛性
Convergence of the Temporal Averages of a Metastable System of Spiking Neurons
论文作者
论文摘要
我们考虑了一个随机的尖峰神经元系统，以前证明，在适当选择参数的意义上，当灭绝的时间渐近不含内存时，当系统中的组件数量渐近地是$ \ iffty $，因此呈现了亚稳态的行为。在本文中，我们通过表明在灭绝之前，我们完成这项工作，因为在适当的时间尺度上采取的时间含量将概率收敛到某种固定值的意义上，系统倾向于稳定。该属性有时称为热化。
We consider a stochastic system of spiking neurons which was previously proven to present a metastable behavior for a suitable choice of the parameter, in the sense that the time of extinction is asymptotically memory-less when the number of components in the system goes to $\infty$. In the present article we complete this work by showing that, previous to extinction, the system tends to stabilize in the sense that temporal means taken on an appropriate time scale converge in probability to some fixed value. This property is sometime called thermalization.
