Spiking neural P systems with homogeneous neurons and synapses

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• 作者：Keqin Jiang^a ; ^{jiangkq0519@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Wenli Chen^a ; ^{chenwl@aqtc.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Yuzhou Zhang^a ; ^{zhangyuzhou@aqtc.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Linqiang Pan^b ; ^{lqpan@mail.hust.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Bio-inspired computing ; Neural-like computational model ; Membrane computing ; P system ; Spiking neural P system
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：1 January 2016
• 年：2016
• 卷：171
• 期：Complete
• 页码：1548-1555
• 全文大小：546 K

文摘

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons process information and communicate by means of spikes, where neurons are different in the sense that they can have different sets of spiking rules. In this work, we consider a variant of SN P systems with two restrictions: (1) all neurons contain only spikes (neurons are homogeneous in this case, since they can be considered as containers of spikes), while the spiking rules are moved on the synapses; (2) all synapses are homogeneous in the sense that each synapse has the same set of rules. These restrictions correspond to the fact that the SN P system consists of only one kind of neurons and one kind of synapses. The computational power of SN P systems with homogeneous neurons and synapses is investigated. Specifically, it is proved that such systems are Turing universal as both number generating and number accepting devices.