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Spiking neural P systems with inhibitory rules

Authors :
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
Research Foundation of the Education Department of Sichuan Province
Peng, Hong
Li, Bo
Wang, Jun
Song, Xiaoxiao
Wang, Tao
Valencia Cabrera, Luis
Pérez Hurtado de Mendoza, Ignacio
Riscos Núñez, Agustín
Pérez Jiménez, Mario de Jesús
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
Research Foundation of the Education Department of Sichuan Province
Peng, Hong
Li, Bo
Wang, Jun
Song, Xiaoxiao
Wang, Tao
Valencia Cabrera, Luis
Pérez Hurtado de Mendoza, Ignacio
Riscos Núñez, Agustín
Pérez Jiménez, Mario de Jesús
Publication Year :
2020

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.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1290385514
Document Type :
Electronic Resource