Affiliations: [a] Key Laboratory of Image Information Processing and Intelligent Control School of Automation, Huazhong University of Science and Technology Wuhan 430074, Hubei, China tfwu@hust.edu.cn | [b] School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou, 450002, China | [c] Key Laboratory of Image Information Processing and Intelligent Control School of Automation, Huazhong University of Science and Technology Wuhan 430074, Hubei, China shixiaolong@mail.hust.edu.cn
Correspondence:
[*]
Address for correspondence: Key Laboratory of Image Information Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
Abstract: Spiking neural (SN, for short) P systems are a class of distributed parallel computing models inspired by the way in which neurons communicate with each other by means of electrical impulses. Recently, a new variant of SN P systems, called SN P systems with homogenous neurons and synapses (HRSSN P systems for short) was proposed, where the spiking and forgetting rules are placed on synapses instead of in neurons and each synapse has the same set of spiking and forgetting rules. This variant of SN P systems has already been proved to be Turing universal as both number generating and accepting devices. In this work, we consider the problem of looking for small universal HRSSN P systems. Specifically, a universal HRRSN P system with standard rules and weight at most 5 having 70 neurons is constructed as a device of computing functions; as a number generator, we find a universal system with standard rules and weight at most 5 having 71 neurons.
