1. Spiking neural P systems with inhibitory rules
- Author
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Xiaoxiao Song, Agustín Riscos-Núñez, Ignacio Pérez-Hurtado, Tao Wang, Luis Valencia-Cabrera, Jun Wang, Bo Li, Hong Peng, Mario J. Pérez-Jiménez, Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial, National Natural Science Foundation of China, Research Fund of Sichuan Science and Technology, Chunhui Project Foundation of the Education Department of China No. Z2016143, and Research Foundation of the Education Department of Sichuan Province
- Subjects
Information Systems and Management ,Computer science ,Structure (category theory) ,02 engineering and technology ,Membrane Computing ,Inhibitory postsynaptic potential ,Topology ,Management Information Systems ,Artificial Intelligence ,020204 information systems ,Completeness (order theory) ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Spiking neural P Systems ,Membrane computing ,Turing ,computer.programming_language ,Directed graph ,State (functional analysis) ,Spiking neural P systems with inhibitory rules ,medicine.anatomical_structure ,Inhibitory synapse ,020201 artificial intelligence & image processing ,Neuron ,computer ,Software - Abstract
Motivated by the mechanism of inhibitory synapses, a new kind of spiking neural P (SNP) system rules, called inhibitory rules, is introduced in this paper. Based on this, a new variant of SNP systems is proposed, called spiking neural P systems with inhibitory rules (SNP-IR systems). Different from the usual firing rules in SNP systems, the firing condition of an inhibitory rule not only depends on the state of the neuron associated with the rule but also is related to the states of other neurons. Moreover, from the perspective of topological structure, the new variant is shown as a directed graph with inhibitory arcs, and therefore seems to have more powerful control. The computational completeness of SNPIR systems is discussed. In particular, it is proved that SNP-IR systems are Turing universal number accepting/generating devices. Moreover, we obtain a small universal function-computing device for SNP-IR systems consisting of 100 neurons. National Natural Science Foundation of China No. 61472328 Research Fund of Sichuan Science and Technology Project No. 2018JY0083 Chunhui Project Foundation of the Education Department of China Nos. Z2016143 Chunhui Project Foundation of the Education Department of China No. Z2016148 Research Foundation of the Education Department of Sichuan Province No. 17TD0034
- Published
- 2020