Based on the feature and communication of neurons in animal neural systems, spiking neural P systems (SN P systems) were proposed as a kind of powerful computing model. Considering the length of axons and the information transmission speed on synapses, SN P systems with delay on synapses (SNP-DS systems) are proposed in this work. Unlike the traditional SN P systems, where all the postsynaptic neurons receive spikes at the same instant from their presynaptic neuron, the postsynaptic neurons in SNP-DS systems would receive spikes at different instants, depending on the delay time on the synapses connecting them. It is proved that the SNP-DS systems are universal as number generators. Two small universal SNP-DS systems, with standard or extended rules, are constructed to compute functions, using 56 and 36 neurons, respectively. Moreover, a simulator has been provided, in order to check the correctness of these two SNP-DS systems, thus providing an experimental validation of the universality of the systems designed.

中文翻译：

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突触延迟的尖峰神经 P 系统

基于动物神经系统中神经元的特性和通信特性，提出了脉冲神经P系统（SN P systems）作为一种强大的计算模型。考虑到轴突的长度和突触上的信息传输速度，本文提出了具有突触延迟的SNP系统（SNP-DS系统）。与所有突触后神经元在同一时刻从其突触前神经元接收到尖峰的传统 SNP 系统不同，SNP-DS 系统中的突触后神经元将在不同时刻接收到尖峰，这取决于连接它们的突触上的延迟时间。证明了 SNP-DS 系统作为数字生成器是通用的。构建了两个具有标准或扩展规则的小型通用 SNP-DS 系统来计算函数，分别使用 56 和 36 个神经元。而且，