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dc.creatorPeng, Honges
dc.creatorLi, Boes
dc.creatorWang, Junes
dc.creatorSong, Xiaoxiaoes
dc.creatorWang, Taoes
dc.creatorValencia Cabrera, Luises
dc.creatorPérez Hurtado de Mendoza, Ignacioes
dc.creatorRiscos Núñez, Agustínes
dc.creatorPérez Jiménez, Mario de Jesúses
dc.date.accessioned2021-02-03T08:40:27Z
dc.date.available2021-02-03T08:40:27Z
dc.date.issued2020
dc.identifier.citationPeng, H., Li, B., Wang, J., Song, X., Wang, T., Valencia Cabrera, L.,...,Pérez Jiménez, M.d.J. (2020). Spiking neural P systems with inhibitory rules. Knowledge-Based Systems, 188 (january 2020, 105064)
dc.identifier.issn0950-7051es
dc.identifier.urihttps://hdl.handle.net/11441/104514
dc.description.abstractMotivated 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.es
dc.description.sponsorshipNational Natural Science Foundation of China No. 61472328es
dc.description.sponsorshipResearch Fund of Sichuan Science and Technology Project No. 2018JY0083es
dc.description.sponsorshipChunhui Project Foundation of the Education Department of China Nos. Z2016143es
dc.description.sponsorshipChunhui Project Foundation of the Education Department of China No. Z2016148es
dc.description.sponsorshipResearch Foundation of the Education Department of Sichuan Province No. 17TD0034es
dc.formatapplication/pdfes
dc.format.extent10es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofKnowledge-Based Systems, 188 (january 2020, 105064)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMembrane Computinges
dc.subjectSpiking neural P Systemses
dc.subjectSpiking neural P systems with inhibitory ruleses
dc.subjectInhibitory synapsees
dc.titleSpiking neural P systems with inhibitory ruleses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDNo. 61472328es
dc.relation.projectIDNo. 2018JY0083es
dc.relation.projectIDNo. Z2016143es
dc.relation.projectIDNo. Z2016148es
dc.relation.projectIDNo. 17TD0034es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0950705119304514es
dc.identifier.doi10.1016/j.knosys.2019.105064es
dc.journaltitleKnowledge-Based Systemses
dc.publication.volumen188es
dc.publication.issuejanuary 2020, 105064es
dc.identifier.sisius21866829es
dc.contributor.funderNational Natural Science Foundation of Chinaes
dc.contributor.funderResearch Fund of Sichuan Science and Technologyes
dc.contributor.funderChunhui Project Foundation of the Education Department of China No. Z2016143es
dc.contributor.funderResearch Foundation of the Education Department of Sichuan Provincees

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