Homogenous spiking neural P systems with anti-spikes
Homogenous spiking neural P systems with anti-spikes
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DOI：
10.1007/s00521-013-1397-8
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发表时间：
2014-06
影响因子：
6
通讯作者：
Tao Song;Xun Wang;Zhujin Zhang;Zhihua Chen
中科院分区：
文献类型：
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作者：
Tao Song;Xun Wang;Zhujin Zhang;Zhihua Chen
带反尖峰脉冲的尖峰神经P系统（Spiking neural P systems with anti-spikes，简称PSPs）是膜计算中的一类类神经计算模型，其灵感来自于神经元通过兴奋性和抑制性脉冲（spikes）进行通信。在这项工作中，我们考虑了一个受限制的变体，称为齐次神经元系统，其中任何神经元都有相同的尖峰和遗忘规则。因此，我们证明了这样的系统可以达到图灵完备性。具体地说，证明了两类纯粹形式的尖峰规则（对于一个尖峰规则，如果控制其应用的正则表达式所对应的语言正是该规则所消耗的尖峰形式，则该规则称为纯粹的）足以计算和接受图灵可计算自然数的集合族。
Spiking neural P systems with anti-spikes (ASN P systems, for short) are a class of neural-like computing models in membrane computing, which are inspired by neurons communication through both excitatory and inhibitory impulses (spikes). In this work, we consider a restricted variant of ASN P systems, called homogeneous ASN P systems, where any neuron has the same set of spiking and forgetting rules. As a result, we prove that such systems can achieve Turing completeness. Specifically, it is proved that two categories of pure form of spiking rules (for a spiking rule, if the language corresponding to the regular expression that controls its application is exactly the form of spikes consumed by the rule, then the rule is called pure) are sufficient to compute and accept the family of sets of Turing computable natural numbers.