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Reversible spiking neural P systems
  • 期刊名称：Frontier of Computer Science in China
  • 时间：2013
  • 页码：350-358
  • 分类：TP273[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置] TQ028.8[化学工程]
  • 作者机构：[1]Key Laboratory of Image Information Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan 430014, China
  • 相关基金：This work was supported by the National Natural Science Foundation of China （61033003; 61100145; 91130034） and the China Postdoctoral Science Foundation （2014M550389）.
  • 相关项目：基于细胞（膜和核酸）的计算模型和算法研究
作者： Tao Song|Tao Song|Xiaolong Shi|Xiaolong Shi|Jinbang Xu|Jinbang Xu|
关键词： 尖峰脉冲, 膜系统, 神经元, 优先权, 受体, ASN, 典型特征, 时间单位, membrane computing, spiking neural P system, Turing completeness, register machine, anti-spike.
中文摘要：

Spiking neural P systems with anti-spikes(ASN P systems) are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes will immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, called ASN P systems without annihilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation will consume one time unit. As a result, such systems using two categories of spiking rules(identified by(a, a) and(a, ˉa)) can achieve Turing completeness as number accepting devices.

英文摘要：

Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.

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