Certain classes of generating functions for the Jacobi and related hypergeometric polynomials

For a certain class of generalized hypergeometric polynomials, the authors first derive a general theorem on bilinear, bilateral, and mixed multilateral generating functions and then apply these generating functions in order to deduce the corresponding results for the classical Jacobi and Laguerre polynomials. They also consider several linear generating functions for these polynomials as well as for some multivariable Jacobi and multivariable Laguerre polynomials which were investigated in recent years. Some of the linear generating functions, presented in this paper, are associated with the Stirling numbers of the second kind.     

On a multivariable extension of Jacobi matrix polynomials

The classical Jacobi matrix polynomials only for commutative matrices were first studied by Defez et al. [E. Defez, L. Jódar, A. Law. Jacobi matrix differential equation, polynomial solutions and their properties, Comput. Math. Appl. 48 (2004) 789–803]. The main aim of this paper is to construct a multivariable extension with the help of the classical Jacobi matrix polynomials (JMPs). Generating matrix functions and recurrence relations satisfied by these multivariable matrix polynomials are derived. Furthermore, general families of multilinear and multilateral generating matrix functions are obtained and their applications are presented.     

三角域上双变量Chebyshev 多项式及其与Bernstein 基的转换

为了更好的解决三角域上的Bézier 曲面在CAGD 中的最佳一致逼近问题, 构造出了三角域上的双变量Chebyshev 正交多项式,研究了与单变量Chebyshev 多项式相类 似的性质,并且给出了三角域上双变量Chebyshev 基和Bernstein 基的相互转换矩阵。通过 实例比较双变量Chebyshev 多项式与双变量Bernstein 多项式以及双变量Jacobi 多项式的最 小零偏差的大小,阐述了双变量Chebyshev 多项式的最小零偏差性。     

Optimal Spectral-Galerkin Methods Using Generalized Jacobi Polynomials

We extend the definition of the classical Jacobi polynomials withindexes α, β>−1 to allow α and/or β to be negative integers. We show that the generalized Jacobi polynomials, with indexes corresponding to the number of boundary conditions in a given partial differential equation, are the natural basis functions for the spectral approximation of this partial differential equation. Moreover, the use of generalized Jacobi polynomials leads to much simplified analysis, more precise error estimates and well conditioned algorithms.Mathematics subject classification 1991. 65N35, 65N22, 65F05, 35J05     

Jacobi–Gauss–Lobatto collocation approach for non-singular variable-order time fractional generalized Kuramoto–Sivashinsky equation

This paper introduces the non-singular variable-order (VO) time fractional version of the generalized Kuramoto–Sivashinsky (GKS) equation with the aid of fractional differentiation in the Caputo–Fabrizio sense. The Jacobi–Gauss–Lobatto collocation technique is developed for solving this equation. More precisely, the derivative matrix of the classical Jacobi polynomials and the VO fractional derivative matrix of the shifted Jacobi polynomials (which is obtained in this study) together with the collocation technique are used to transform the solution of problem into the solution of an algebraic system of equations. Numerical simulations for several test problems have been shown to accredit the established algorithm.

     

Biorthogonal matrix polynomials related to Jacobi matrix polynomials

In this paper, we define the pair of biorthogonal matrix polynomials suggested by the Jacobi matrix polynomials. Biorthogonality property, matrix generating functions and matrix recurrence relations are given.     

Solutions of convolution integral and integral equations via double general orthogonal polynomials

Double general orthogonal polynomials are developed in this work to approximate the solutions of convolution integrals, Volterra integral equations, and Fredholm integral equations. The proposed method reduces the computations of integral equations to the successive solution of a set of linear algebraic equations in matrix form; thus, the computational complexity is considerably simplified. Furthermore, the solutions obtained by the general orthogonal polynomials include as special cases solutions by Chebyshev polynomials, Legendre polynomials, Laguerre polynomials, or Jacobi polynomials. A comparison of the results obtained via several different classical orthogonal polynomial approximations is also presented.     

Adomian decomposition method by Gegenbauer and Jacobi polynomials

In this paper, orthogonal polynomials on [–1,1] interval are used to modify the Adomian decomposition method (ADM). Gegenbauer and Jacobi polynomials are employed to improve the ADM and compared with the method of using Chebyshev and Legendre polynomials. To show the efficiency of the developed method, some linear and nonlinear examples are solved by the proposed method, results are compared with other modifications of the ADM and the exact solutions of the problems.     

Computations with quasiseparable polynomials and matrices

In this paper, we survey several recent results that highlight an interplay between a relatively new class of quasiseparable matrices and univariate polynomials. Quasiseparable matrices generalize two classical matrix classes, Jacobi (tridiagonal) matrices and unitary Hessenberg matrices that are known to correspond to real orthogonal polynomials and Szegö polynomials, respectively. The latter two polynomial families arise in a wide variety of applications, and their short recurrence relations are the basis for a number of efficient algorithms. For historical reasons, algorithm development is more advanced for real orthogonal polynomials. Recent variations of these algorithms tend to be valid only for the Szegö polynomials; they are analogues and not generalizations of the original algorithms.     

Analysis and optimal control of linear time-varying systems via general orthogonal polynomials

The operational matrix consisting of the product of two time functions, and the operational matrices for forward or backward integration consisting of general orthogonal polynomials are derived, respectively, for the analysis and optimal control of linear time-varying systems with a quadratic performance measure. The present results include results obtained via Chebyshev, Legendre, Laguerre, Jacobi, Hermite and ultraspherical polynomials as special cases.     

Error Analysis for Mapped Jacobi Spectral Methods

Approximation properties of mapped Jacobi polynomials and of interpolations based on mapped Jacobi–Gauss–Lobatto points are established. These results play an important role in numerical analysis of mapped Jacobi spectral methods. As examples of applications, optimal error estimates for several popular regular and singular mappings are derived.Mathematics Subject Classification (1991): 65N35; 65N15; 65N50     

MOPS: Multivariate orthogonal polynomials (symbolically)

In this paper we present a Maple library (MOPS) for computing Jack, Hermite, Laguerre, and Jacobi multivariate polynomials, as well as eigenvalue statistics for the Hermite, Laguerre, and Jacobi ensembles of random matrix theory. We also compute multivariate hypergeometric functions, and offer both symbolic and numerical evaluations for all these quantities.     

Application of shifted Jacobi pseudospectral method for solving (in)finite-horizon min–max optimal control problems with uncertainty

The difficulty of solving the min–max optimal control problems (M-MOCPs) with uncertainty using generalised Euler–Lagrange equations is caused by the combination of split boundary conditions, nonlinear differential equations and the manner in which the final time is treated. In this investigation, the shifted Jacobi pseudospectral method (SJPM) as a numerical technique for solving two-point boundary value problems (TPBVPs) in M-MOCPs for several boundary states is proposed. At first, a novel framework of approximate solutions which satisfied the split boundary conditions automatically for various boundary states is presented. Then, by applying the generalised Euler–Lagrange equations and expanding the required approximate solutions as elements of shifted Jacobi polynomials, finding a solution of TPBVPs in nonlinear M-MOCPs with uncertainty is reduced to the solution of a system of algebraic equations. Moreover, the Jacobi polynomials are particularly useful for boundary value problems in unbounded domain, which allow us to solve infinite- as well as finite and free final time problems by domain truncation method. Some numerical examples are given to demonstrate the accuracy and efficiency of the proposed method. A comparative study between the proposed method and other existing methods shows that the SJPM is simple and accurate.     

Investigating the Orthogonality Conditions of Wavelets Based on Jacobi Polynomials

The properties of wavelets based on Jacobi polynomials are analyzed. The conditions are considered under which these wavelets are mutually orthogonal and under which the wavelet basis is characterized by a minimum Riesz ratio. These problems lead to the solution of systems of nonlinear equations by a method proposed earlier by the authors.     

On some new contiguous relations for the Gauss hypergeometric function with applications

Contiguous relations for hypergeometric series contain an enormous amount of hidden information. Applications of contiguous relations range from the evaluation of hypergeometric series to the derivation of summation and transformation formulas for such series. In this paper, a new set of contiguous function relations are established. Applications of such relations to hypergeometric summation formulas and the theory of Jacobi polynomials are presented.     

Hermite interpolation and mean convergence of its derivatives

Weighted L^p convergence of derivatives of Hermite, interpolation on the zeros of Jacobi polynomials plus additional points is investigated.     

The Relationships Between Chebyshev,Legendre and Jacobi Polynomials: The Generic Superiority of Chebyshev Polynomials and Three Important Exceptions

We analyze the asymptotic rates of convergence of Chebyshev, Legendre and Jacobi polynomials. One complication is that there are many reasonable measures of optimality as enumerated here. Another is that there are at least three exceptions to the general principle that Chebyshev polynomials give the fastest rate of convergence from the larger family of Jacobi polynomials. When $f(x)$ is singular at one or both endpoints, all Gegenbauer polynomials (including Legendre and Chebyshev) converge equally fast at the endpoints, but Gegenbauer polynomials converge more rapidly on the interior with increasing order $m$ . For functions on the surface of the sphere, associated Legendre functions, which are proportional to Gegenbauer polynomials, are best for the latitudinal dependence. Similarly, for functions on the unit disk, Zernike polynomials, which are Jacobi polynomials in radius, are superior in rate-of-convergence to a Chebyshev–Fourier series. It is true, as was conjectured by Lanczos 60 years ago, that excluding these exceptions, the Chebyshev coefficients $a_{n}$ usually decrease faster than the Legendre coefficients $b_{n}$ by a factor of $\sqrt{n}$ . We calculate the proportionality constant for a few examples and restrictive classes of functions. The more precise claim that $b_{n} \sim \sqrt{\pi /2} \sqrt{n} a_{n}$ , made by Lanczos and later Fox and Parker, is true only for rather special functions. However, individual terms in the large $n$ asymptotics of Chebyshev and Legendre coefficients usually do display this proportionality.     

A novel algorithm for explicit optimal multi-degree reduction of triangular surfaces

This paper introduces the algebraic property of bivariate orthonormal Jacobi polynomials into geometric approximation. Based on the latest results on the transformation formulae between bivariate Bernstein polynomials and Jacobi polynomials, we naturally deduce a novel algorithm for multi-degree reduction of triangular B~zier surfaces. This algorithm possesses four characteristics： ability of error forecast, explicit expression, less time consumption, and best precision. That is, firstly, whether there exists a multi-degree reduced surface within a prescribed tolerance is judged beforehand; secondly, all the operations of multi-degree reduction are just to multiply the column vector generated by sorting the series of the control points of the original surface in lexicographic order by a matrix; thirdly, this matrix can be computed at one time and stored in an array before processing degree reduction; fourthly, the multi-degree reduced surface achieves an optimal approximation in the norm L2. Some numerical experiments are presented to validate the effectiveness of this algorithm, and to show that the algorithm is applicable to information processing of products in CAD system.     

The use of Jacobi polynomials in the numerical solution of coupled system of fractional differential equations

In this paper, we study shifted Jacobi polynomials and develop a simple but highly accurate scheme for the numerical solution of coupled system of fractional differential equations. We derive some operational matrices of integration and differentiation of fractional order. By the application of these matrices we provide a theoretical treatment to approximate the solutions of the corresponding system. We use Matlab to perform necessary operations. The applicability of the technique is shown with some examples and the results are displayed graphically.