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dc.contributor.authorFord, Neville J.*
dc.contributor.authorLima, Pedro M.*
dc.contributor.authorLumb, Patricia M.*
dc.date.accessioned2016-08-31T12:06:31Z
dc.date.available2016-08-31T12:06:31Z
dc.date.issued2016-09-08
dc.identifier.citationFord, N. J., Lima, P. M., & Lumb, P. M. (2017). Numerical investigation of noise induced changes to the solution behaviour of the discrete FitzHugh–Nagumo equation. Applied Mathematics and Computation, 293, 448-460. doi: http://dx.doi.org/10.1016/j.amc.2016.08.035en
dc.identifier.issn0096-3003
dc.identifier.doi10.1016/j.amc.2016.08.035
dc.identifier.urihttp://hdl.handle.net/10034/619088
dc.description.abstractIn this work we introduce and analyse a stochastic functional equation, which contains both delayed and advanced arguments. This equation results from adding a stochastic term to the discrete FitzHugh-Nagumo equation which arises in mathematical models of nerve conduction. A numerical method is introduced to compute approximate solutions and some numerical experiments are carried out to investigate their dynamical behaviour and compare them with the solutions of the corresponding deterministic equation.
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAn error occurred on the license name.*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectstochastic mixed-type functional differential equationen
dc.subjectEuler-Maruyama methoden
dc.titleNumerical investigation of noise induced changes to the solution behaviour of the discrete FitzHugh-Nagumo equationen
dc.typeArticleen
dc.contributor.departmentUniversity of Chester, Instituto Superior Tecnico, University of Lisbon, University of Chesteren
dc.identifier.journalApplied Mathematics and Computation
dc.date.accepted2016-08-19
or.grant.openaccessYesen
rioxxterms.funderSantander Universitiesen
rioxxterms.identifier.projectInternational Research Excellence Award, 2014-15en
rioxxterms.versionAMen
rioxxterms.licenseref.startdate2017-09-08
html.description.abstractIn this work we introduce and analyse a stochastic functional equation, which contains both delayed and advanced arguments. This equation results from adding a stochastic term to the discrete FitzHugh-Nagumo equation which arises in mathematical models of nerve conduction. A numerical method is introduced to compute approximate solutions and some numerical experiments are carried out to investigate their dynamical behaviour and compare them with the solutions of the corresponding deterministic equation.
rioxxterms.publicationdate2016-09-08


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