Evaluation of numerical integration schemes for a partial integro-differential equation

Simple item page
dc.contributor.authorElvin, A.
dc.contributor.authorLaing, C.
dc.date.accessioned2013-05-15T02:16:28Z
dc.date.available2013-05-15T02:16:28Z
dc.date.issued2005
dc.description.abstractNumerical methods are important in computational neuroscience where complex nonlinear systems are studied. This report evaluates two methodologies, finite differences and Fourier series, for numerically integrating a nonlinear neural model based on a partial integro-differential equation. The stability and convergence criteria of four finite difference methods is investigated and their efficiency determined. Various ODE solvers in Matlab are used with the Fourier series method to solve the neural model, with an evaluation of the accuracy of the approximation versus the efficiency of the method. The two methodologies are then compared.en
dc.identifier.citationElvin, A., Laing, C. (2005), Evaluation of numerical integration schemes for a partial integro-differential equation, Research Letters in the Information and Mathematical Sciences, 7, 171-186en
dc.identifier.issn1175-2777
dc.identifier.urihttp://hdl.handle.net/10179/4444
dc.language.isoenen
dc.publisherMassey Universityen
dc.subjectNeural modelsen
dc.titleEvaluation of numerical integration schemes for a partial integro-differential equationen
dc.typeArticleen
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Evaluation_of_numerical_integration_schemes_for_a_partial_integro-differential_equation.pdf
Size:
425.95 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Research Letters in the Information and Mathematical Sciences