Spectral Methods for Substantial Fractional Differential Equations
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 1554-1574 |
Journal / Publication | Journal of Scientific Computing |
Volume | 74 |
Issue number | 3 |
Online published | 19 Jul 2017 |
Publication status | Published - Mar 2018 |
Link(s)
Abstract
In this paper, a non-polynomial spectral Petrov–Galerkin method and its associated collocation method for substantial fractional differential equations are proposed, analyzed, and tested. We modify a class of generalized Laguerre polynomials to form our trial basis and test basis. After a proper scaling of these bases, our Petrov–Galerkin method results in diagonal and well-conditioned linear systems for certain types of fractional differential equations. In the meantime, we provide superconvergence points of the Petrov–Galerkin approximation for associated fractional derivative and function value of true solution. Additionally, we present explicit fractional differential collocation matrices based upon Laguerre–Gauss–Radau points. It is noteworthy that the proposed methods allow us to adjust a parameter in the basis according to different given data to maximize the convergence rate. All these findings have been proved rigorously in our convergence analysis and confirmed in our numerical experiments.
Research Area(s)
- Collocation method, Generalized Laguerre polynomials, Petrov–Galerkin, Spectral method, Substantial fractional differential equation, Superconvergence
Citation Format(s)
Spectral Methods for Substantial Fractional Differential Equations. / Huang, Can; Zhang, Zhimin; Song, Qingshuo.
In: Journal of Scientific Computing, Vol. 74, No. 3, 03.2018, p. 1554-1574.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review