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dc.contributor.authorHardiman, Kory
dc.date.accessioned2014-07-30T12:34:23Z
dc.date.available2014-07-30T12:34:23Z
dc.date.issued2014-07-30
dc.identifier.urihttp://hdl.handle.net/10222/53132
dc.description.abstractThis thesis provides a comparison between sequential and event-driven network simulation outcomes for biological control networks. A comparison is made between the effects of order of operation on these networks based on the two models. The sequential network model provides a serial processing approach using the Java programming language. The event-driven network model is executed using software manufactured by Trihedral Engineering Limited, called Visual Tag System (VTS). The thesis first describes any research completed in this area to date. Next, the thesis provides a detailed explanation of the mathematical model of the two different networks (sequential and event-driven) and the simulation strategies employed to obtain results. This is followed by a detailed analysis of the simulation outcomes. In addition, the models for sequential and event-driven both consider network plasticity and neural plasticity. Phenomena such as an ischemic event (heart attack) and the idea of twins’ neural responses are examined.en_US
dc.language.isoenen_US
dc.subjectEvent-driven Simulationen_US
dc.subjectBiological Control Networksen_US
dc.subjectEffects of Order of Operationen_US
dc.titleSEQUENTIAL VERSUS EVENT-DRIVEN CONTROL NETWORKS: THE EFFECTS OF ORDER OF OPERATION WITH EXAMPLES FROM BIOLOGYen_US
dc.date.defence2014-07-25
dc.contributor.departmentDepartment of Engineering Mathematics & Internetworkingen_US
dc.contributor.degreeMaster of Scienceen_US
dc.contributor.external-examinerN/Aen_US
dc.contributor.graduate-coordinatorDr. Guy Kemberen_US
dc.contributor.thesis-readerDr. Gordon Fentonen_US
dc.contributor.thesis-readerDr. Geoff Maksymen_US
dc.contributor.thesis-supervisorDr. Guy Kemberen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.copyright-releaseNot Applicableen_US
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