Computational aspects of fractional Romanovski–Bessel functions

Nowadays, various groups of classical orthogonal polynomials are part of several spectral algorithms for basic mathematical machinery. It is well known that the polynomial-based spectral methods can provide high accuracy for partial differential equations with smooth solutions, but may not have any advantage when the solutions exhibit weakly singular behavior. However, to establish accurate spectral schemes for problems with non-smooth solutions, one has to enrich the polynomial-based approximation space by introducing special functions that capture the singular behavior of the underlying problem. The main purpose of this paper is to introduce a new finite class of orthogonal functions based on the Romanovski–Bessel polynomials, and to investigate their basic general properties such as the fractional Romanovski–Bessel–Gauss-type quadrature formulae together with fundamental results of approximation for certain weighted projection operators for certain weighted projection operators described in suitable weighted Sobolev spaces. The relationship between such new orthogonal finite set of functions and the other families of infinite fractional orthogonal functions such as fractional Laguerre functions and generalized Laguerre fractional modified functions are derived.

[1]  M. Zaky Existence, uniqueness and numerical analysis of solutions of tempered fractional boundary value problems , 2019, Applied Numerical Mathematics.

[2]  Ibrahem G. Ameen,et al.  On the rate of convergence of spectral collocation methods for nonlinear multi-order fractional initial value problems , 2019, Computational and Applied Mathematics.

[3]  Jie Shen,et al.  Spectral Methods: Algorithms, Analysis and Applications , 2011 .

[4]  Rene F. Swarttouw,et al.  Orthogonal polynomials , 2020, NIST Handbook of Mathematical Functions.

[5]  J. Sousa,et al.  The $$\psi $$-Hilfer fractional calculus of variable order and its applications , 2020, Comput. Appl. Math..

[6]  R. S. Costas-Santos,et al.  q-Classical Orthogonal Polynomials: A General Difference Calculus Approach , 2006, math/0612097.

[7]  J. Machado,et al.  Solving nonlinear systems of fractional-order partial differential equations using an optimization technique based on generalized polynomials , 2020, Computational and Applied Mathematics.

[8]  E. Capelas de Oliveira,et al.  On the ψ -Hilfer fractional derivative , 2018, Communications in Nonlinear Science and Numerical Simulation.

[9]  Mahmoud A. Zaky,et al.  Recovery of high order accuracy in Jacobi spectral collocation methods for fractional terminal value problems with non-smooth solutions , 2019, J. Comput. Appl. Math..

[10]  J. Vanterler da C. Sousa,et al.  On the ψ-Hilfer fractional derivative , 2017, Commun. Nonlinear Sci. Numer. Simul..

[11]  Y. Wang,et al.  Chebyshev spectral methods for multi-order fractional neutral pantograph equations , 2020 .

[12]  E. H. Doha,et al.  On Romanovski–Jacobi polynomials and their related approximation results , 2020, Numerical Methods for Partial Differential Equations.

[13]  J.A. Tenreiro Machado,et al.  A spectral framework for fractional variational problems based on fractional Jacobi functions , 2018, Applied Numerical Mathematics.

[14]  E. H. Doha,et al.  Spectral Solutions for Differential and Integral Equations with Varying Coefficients Using Classical Orthogonal Polynomials , 2018, Bulletin of the Iranian Mathematical Society.

[15]  M. Masjed‐Jamei Three Finite Classes of Hypergeometric Orthogonal Polynomials and Their Application in Functions Approximation , 2002 .