Novel Numerical Spiking Neural P Systems with a Variable Consumption Strategy

dc.contributor.authorYin, Xiu
dc.contributor.authorLiu, Xiyu
dc.contributor.authorSun, Minghe
dc.contributor.authorRen, Qianqian
dc.date.accessioned2021-04-19T15:26:58Z
dc.date.available2021-04-19T15:26:58Z
dc.date.issued2021-03-20
dc.date.updated2021-04-19T15:26:59Z
dc.description.abstractA novel variant of NSN P systems, called numerical spiking neural P systems with a variable consumption strategy (NSNVC P systems), is proposed. Like the spiking rules consuming spikes in spiking neural P systems, NSNVC P systems introduce a variable consumption strategy by modifying the form of the production functions used in NSN P systems. Similar to the delay feature of the spiking rules, NSNVC P systems introduce a postponement feature into the production functions. The execution of the production functions in NSNVC P systems is controlled by two, i.e., polarization and threshold, conditions. Multiple synaptic channels are used to transmit the charges and the production values in NSNVC P systems. The proposed NSNVC P systems are a type of distributed parallel computing models with a directed graphical structure. The Turing universality of the proposed NSNVC P systems is proved as number generating/accepting devices. Detailed descriptions are provided for NSNVC P systems as number generating/accepting devices. In addition, a universal NSNVC P system with 66 neurons is constructed as a function computing device.
dc.description.departmentManagement Science and Statistics
dc.identifierdoi: 10.3390/pr9030549
dc.identifier.citationProcesses 9 (3): 549 (2021)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/552
dc.rightsAttribution 4.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectmembrane computing
dc.subjectnumerical spiking neural P systems
dc.subjectvariable consumption strategy
dc.subjectpostponement features
dc.subjectTuring universality
dc.titleNovel Numerical Spiking Neural P Systems with a Variable Consumption Strategy
dc.typeArticleen_US

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