1 Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China.
* Department of Computer Science, Faculty of Mathematics and Computer Science, University of Bucharest, Str. Academiei Nr. 14, Sector 1, C.P. 010014, Bucharest, Romania.
Int J Neural Syst. 2018 Oct;28(8):1850013. doi: 10.1142/S0129065718500132. Epub 2018 Apr 2.
Spiking neural P systems are a class of third generation neural networks belonging to the framework of membrane computing. Spiking neural P systems with communication on request (SNQ P systems) are a type of spiking neural P system where the spikes are requested from neighboring neurons. SNQ P systems have previously been proved to be universal (computationally equivalent to Turing machines) when two types of spikes are considered. This paper studies a simplified version of SNQ P systems, i.e. SNQ P systems with one type of spike. It is proved that one type of spike is enough to guarantee the Turing universality of SNQ P systems. Theoretical results are shown in the cases of the SNQ P system used in both generating and accepting modes. Furthermore, the influence of the number of unbounded neurons (the number of spikes in a neuron is not bounded) on the computation power of SNQ P systems with one type of spike is investigated. It is found that SNQ P systems functioning as number generating devices with one type of spike and four unbounded neurons are Turing universal.
尖峰神经网络系统是第三代神经网络的一个分支，属于膜计算框架。具有请求式通信的尖峰神经网络系统 (SNQP 系统) 是一种尖峰神经网络系统，其中尖峰是从相邻神经元请求的。当考虑两种类型的尖峰时，已经证明 SNQP 系统是通用的（在计算上等同于图灵机）。本文研究了 SNQP 系统的简化版本，即只有一种类型的尖峰的 SNQP 系统。证明了一种类型的尖峰足以保证 SNQP 系统的图灵通用性。在生成和接受模式下使用的 SNQP 系统的情况下展示了理论结果。此外，还研究了具有一种类型的尖峰的 SNQP 系统中无界神经元的数量（一个神经元中的尖峰数量不受限制）对其计算能力的影响。结果发现，具有一种类型的尖峰和四个无界神经元的作为数字生成设备的 SNQP 系统是图灵通用的。
