Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/62429
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dc.contributor.authorAllison, A.-
dc.contributor.authorAbbott, D.-
dc.contributor.authorPearce, C.-
dc.date.issued2009-
dc.identifier.citationAustralia and New Zealand Industrial and Applied Mathematics (ANZIAM) Journal, 2009; 51(SUPPL.):C747-C767-
dc.identifier.issn1446-1811-
dc.identifier.issn1446-8735-
dc.identifier.urihttp://hdl.handle.net/2440/62429-
dc.descriptionProceedings of the Engineering Mathematics and Applications Conference held in Adelaide, Australia, 6-9 December 2010.-
dc.description.abstractWe derive approximate numerical solutions for an ordinary differential equation common in engineering using two different types of basis functions, polynomial and Gaussian, and a maximum discrepancy error measure. We compare speed and accuracy of the two solutions. The basic finding for our example is that while Gaussian basis functions can be used, the computational effort is greater than that required for a polynomial basis given the same degree of error.-
dc.description.statementofresponsibilityA. Allison, D. Abbott and C.E.M. Pearce-
dc.language.isoen-
dc.publisherAustralian Mathematical Society-
dc.rightsCopyright Austral. Mathematical Society 2010-
dc.source.urihttp://anziamj.austms.org.au/ojs/index.php/ANZIAMJ/article/view/2630-
dc.titleGaussian basis functions for solving differential equations-
dc.typeJournal article-
pubs.publication-statusPublished-
dc.identifier.orcidAllison, A. [0000-0003-3865-511X]-
dc.identifier.orcidAbbott, D. [0000-0002-0945-2674]-
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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