2019
DOI: 10.1002/mma.5627
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Numerical solution of multiterm variable‐order fractional differential equations via shifted Legendre polynomials

Abstract: In this paper, shifted Legendre polynomials will be used for constructing the numerical solution for a class of multiterm variable‐order fractional differential equations. In the proposed method, the shifted Legendre operational matrix of the fractional variable‐order derivatives will be investigated. The fundamental problem is reduced to an algebraic system of equations using the constructed matrix and the collocation technique, which can be solved numerically. The error estimate of the proposed method is inv… Show more

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Cited by 87 publications
(49 citation statements)
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References 42 publications
(80 reference statements)
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“…e history of fractional calculus is not very much old, but in the short span of time, it experienced a rapid development. Recently, the generalizations [15][16][17][18][19][20][21][22][23][24][25], extensions [26][27][28][29][30][31][32], and applications [33][34][35][36][37][38][39][40][41][42][43][44][45][46] for fractional calculus have been made by many researchers.…”
Section: Introductionmentioning
confidence: 99%
“…e history of fractional calculus is not very much old, but in the short span of time, it experienced a rapid development. Recently, the generalizations [15][16][17][18][19][20][21][22][23][24][25], extensions [26][27][28][29][30][31][32], and applications [33][34][35][36][37][38][39][40][41][42][43][44][45][46] for fractional calculus have been made by many researchers.…”
Section: Introductionmentioning
confidence: 99%
“…C2 0 < lim inf n→∞ α n ≤ lim sup n→∞ α n < 1; C3 0 < lim inf n→∞ β n ≤ lim sup n→∞ β n < 1; C4 lim inf n→∞ r n > 0; C5 0 < lim inf n→∞ s n ≤ lim sup n→∞ s n < 2α. Then the sequence {x n } generated by (27) weakly converges to a pointq ∈ Γ . H 1 → H 1 be an α-inverse strongly monotone operator and B : H 1 → 2 H 1 be a maximally monotone operator.…”
Section: Corollary 33 Letmentioning
confidence: 99%
“…In many fractional-order models, the analytical solution is more complicated, therefore the numerical solutions for these models are appropriate [1,6,20]. These numerical so-lutions depend on several techniques such as finite difference, finite volume, variational iteration, Legendre polynomials, Chebyshev collocation, homotopy perturbation, operational matrix, variational iteration, Adams-Bashforth, nonstandard finite difference, sinccollocation, compact finite difference, tau method, block pulse, decomposition, radial basis, Taylor collocation, and wavelets spectral (see, for example, [5,11,24,25,35,38]).…”
Section: Introductionmentioning
confidence: 99%