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Publication:
High-Order Finite Volume Approximation for Population Density Model Based on Quadratic Integrate-and Neuron

dc.authorscopusid57202809964
dc.authorscopusid57213856627
dc.authorscopusid10639356300
dc.contributor.authorSingh, P.
dc.contributor.authorKumar, S.
dc.contributor.authorKoksal, Mehmet Emir
dc.date.accessioned2020-06-21T13:05:27Z
dc.date.available2020-06-21T13:05:27Z
dc.date.issued2019
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Singh] Paramjeet, School of Mathematics, Thapar Institute of Engineering & Technology, Patiala, PB, India; [Kumar] Santosh, School of Mathematics, Thapar Institute of Engineering & Technology, Patiala, PB, India; [Koksal] Mehmet Emir, Department of Mathematics, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractPurpose: The purpose of this paper is to develop and apply a high-order numerical method based on finite volume approximation for quadratic integrate-and-fire (QIF) neuron model with the help of population density approach. Design/methodology/approach: The authors apply the population density approach for the QIF neuron model to derive the governing equation. The resulting mathematical model cannot be solved with existing analytical or numerical techniques owing to the presence of delay and advance. The numerical scheme is based along the lines of approximation: spatial discretization is performed by weighted essentially non-oscillatory (WENO) finite volume approximation (FVM) and temporal discretization are performed by strong stability-preserving explicit Runge–Kutta (SSPERK) method. Compared with existing schemes of orders 2 and 3 from the literature, the proposed scheme is found to be more efficient and it produces accurate solutions with few grid cells. In addition to this, discontinuity is added in the application of the model equation to illustrate the high performance of the proposed scheme. Findings: The developed scheme works nicely for the simulation of the resulting model equation. The authors discussed the role of inhibitory and excitatory parts in variation of neuronal firing. The validation of the designed scheme is measured by its comparison with existing schemes in the literature. The efficiency of the designed scheme is demonstrated via numerical simulations. Practical implications: It is expected that the present study will be a useful tool to tackle the complex neuron model and related studies. Originality/value: The novel aspect of this paper is the application of the numerical methods to study the modified version of leaky integrate-and-fire neuron based on a QIF neuron. The model of the current study is inspired from the base model given in Stein (1965) and modified version in Kadalbajoo and Sharma (2005) and Wang and Zhang (2014). The applicability was confirmed by taking some numerical examples. © 2018, Emerald Publishing Limited.en_US
dc.identifier.doi10.1108/EC-11-2017-0445
dc.identifier.endpage102en_US
dc.identifier.issn0264-4401
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85057127220
dc.identifier.scopusqualityQ3
dc.identifier.startpage84en_US
dc.identifier.urihttps://doi.org/10.1108/EC-11-2017-0445
dc.identifier.volume36en_US
dc.identifier.wosWOS:000458733000004
dc.identifier.wosqualityQ2
dc.language.isoenen_US
dc.publisherEmerald Group Holdings Ltd.en_US
dc.relation.ispartofEngineering Computationsen_US
dc.relation.journalEngineering Computationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDifferential Difference Equationen_US
dc.subjectFinite Volume Approximationen_US
dc.subjectQuadratic Integrate-and-Fire Neuronen_US
dc.titleHigh-Order Finite Volume Approximation for Population Density Model Based on Quadratic Integrate-and Neuronen_US
dc.typeArticleen_US
dspace.entity.typePublication

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