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dc.contributor.advisorFord, Neville J.
dc.contributor.authorLumb, Patricia M.*
dc.date.accessioned2009-05-19T15:40:54Z
dc.date.available2009-05-19T15:40:54Z
dc.date.issued2004-04
dc.identifieruk.bl.ethos.402267
dc.identifier.urihttp://hdl.handle.net/10034/68595
dc.description.abstractThis thesis concerns the development of a method for the detection of small solutions to delay differential equations. The detection of small solutions is important because their presence has significant influence on the analytical prop¬erties of an equation. However, to date, analytical methods are of only limited practical use. Therefore this thesis focuses on the development of a reliable new method, based on finite order approximations of the underlying infinite dimen¬sional problem, which can detect small solutions. Decisions (concerning the existence, or otherwise, of small solutions) based on our visualisation technique require an understanding of the underlying methodol¬ogy behind our approach. Removing this need would be attractive. The method we have developed can be automated, and at the end of the thesis we present a prototype Matlab code for the automatic detection of small solutions to delay differential equations.
dc.language.isoenen
dc.publisherUniversity of Liverpool (Chester College of Higher Education)en
dc.subjectdelay differential equationsen
dc.titleDelay differential equations: Detection of small solutionsen
dc.typeThesis or dissertationen
dc.publisher.departmentUniversity College Chesteren
dc.type.qualificationnamePhDen
dc.type.qualificationlevelDoctoralen
html.description.abstractThis thesis concerns the development of a method for the detection of small solutions to delay differential equations. The detection of small solutions is important because their presence has significant influence on the analytical prop¬erties of an equation. However, to date, analytical methods are of only limited practical use. Therefore this thesis focuses on the development of a reliable new method, based on finite order approximations of the underlying infinite dimen¬sional problem, which can detect small solutions. Decisions (concerning the existence, or otherwise, of small solutions) based on our visualisation technique require an understanding of the underlying methodol¬ogy behind our approach. Removing this need would be attractive. The method we have developed can be automated, and at the end of the thesis we present a prototype Matlab code for the automatic detection of small solutions to delay differential equations.
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