Spiking Neural P Systems with Extended Rules
Spiking Neural P Systems with Extended Rules
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发表时间：
2006
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通讯作者：
Haiming Cheng;Tseren-Onolt Ishdorj;G. Paun
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作者：
Haiming Cheng;Tseren-Onolt Ishdorj;G. Paun
我们认为尖峰神经P系统的尖峰规则允许引入零，一个或多个尖峰在同一时间。所获得的系统的计算能力进行了调查，当考虑到它们作为数字生成和语言生成设备。在第一种情况下，得到了一个更简单的普适性证明（对于限制规则来说，普适性是已知的），而在后一种情况下，我们找到了有限和递归可重复语言的特征（不使用任何压缩机制，因为在限制规则的情况下是必要的）。与正规语言的关系也进行了研究。文章最后给出了一个用语言计算某些运算的工具箱。
We consider spiking neural P systems with spiking rules allowed to introduce zero, one, or more spikes at the same time. The computing power of the obtained systems is investigated, when considering them as number generating and as language generating devices. In the first case, a simpler proof of universality is obtained (universality is already known for the restricted rules), while in the latter case we find characterizations of finite and recursively enumerable languages (without using any squeezing mechanism, as it was necessary in the case of restricted rules). The relationships with regular languages are also investigated. In the end of the paper, a tool-kit for computing (some) operations with languages is provided.