Small Universal Sequential Spiking Neural P Systems based on Minimum Spike Number
Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. Recently, a variant of SN P systems was considered: at each step the neuron with the minimum number of spikes among the neurons that can spike will fire. In previous literature, it was obtained that such systems can achieve Turing completeness when the computing result is realized through accumulation of spikes in the output neuron. In this work, we use a natural way to define the computing result of the systems, by means of determining the time interval between the first two spikes emitted by the output neuron. As devices of computing functions, we construct a universal sequential SN P system based on minimum spike number (without delay) by using 137 neurons; as generators of sets of numbers, a universal sequential SN P system based on minimum spike number (without delay) with 126 neurons is also obtained.
Membrane computing Spiking neural P system Sequentiality Small universal system
Keqin Jiang Yufang Huang Jinbang Xu Zhihua Chen
Key Laboratory of Image Processing and Intelligent Control,School of Automation,Huazhong University Key Laboratory of Image Processing and Intelligent Control,School of Automation,Huazhong University Key Laboratory of Image Processing and Intelligent Control,School of Automation,Huazhong University
国际会议
成都
英文
89-104
2013-11-04（万方平台首次上网日期，不代表论文的发表时间）