Small Universal Spiking Neural P Systems Working in Exhaustive Mode
Small Universal Spiking Neural P Systems Working in Exhaustive Mode
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DOI：
10.1109/tnb.2011.2160281
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发表时间：
2011-06
影响因子：
3.9
通讯作者：
L. Pan;Xiangxiang Zeng
中科院分区：
文献类型：
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作者：
L. Pan;Xiangxiang Zeng
脉冲神经P系统是一类分布式并行计算设备，其灵感来自于神经元通过脉冲进行通信的方式。本文在脉冲神经P系统的框架下研究了寻找小型通用计算设备的问题。提出了一种用脉冲神经P系统来模拟寄存器机的新方法，即用一个神经元来模拟寄存器机的所有指令，从而用较少的神经元来构造工作在穷举模式下的通用脉冲神经P系统.具体地，构造了一个具有36个神经元的通用脉冲神经P系统，该系统工作在穷举模式下。这显著改善了已知的结果，其中使用了125个神经元。
Spiking neural P systems are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this paper, the problem of looking for small universal computing devices is investigated in the framework of spiking neural P systems. A new approach is introduced to simulate register machines by spiking neural P systems, where only one neuron is used for all instructions of the simulated register machine; in this way, less neurons are used to construct universal spiking neural P systems working in exhaustive mode. Specifically, a universal spiking neural P system with 36 neurons is constructed, which works in exhaustive mode. This significantly improves the already known result, where 125 neurons are used.