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

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    Abstract
    Numerical 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.
    Citation
    Elvin, A., Laing, C. (2005), Evaluation of numerical integration schemes for a partial integro-differential equation, Research Letters in the Information and Mathematical Sciences, 7, 171-186
    Date
    2005
    Author
    Elvin, A.
    Laing, C.
    Publisher
    Massey University
    URI
    http://hdl.handle.net/10179/4444
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    • Research Letters in the Information and Mathematical Sciences
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