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It is demonstrated how an explicit expression of the (partial) sum of Tetranacci numbers can be found and proved using generating functions and the Hadamard product. We also provide a Binet-type formula for generalized Fibonacci numbers, by…

Number Theory · Mathematics 2020-01-22 Helmut Prodinger , Sarah J. Selkirk

The aim of this paper is to construct general forms of ordinary generating functions for special numbers and polynomials involving Fibonacci type numbers and polynomials, Lucas numbers and polynomials, Chebyshev polynomials, Sextet…

General Mathematics · Mathematics 2023-06-16 Yilmaz Simsek

The goal of this communication is to propose a generalized notion of the "traditional derivative". This generalization includes the fractional derivatives such as the Riemann-Liouville, Gruenwald-Letnikov, Weyl, Riesz, Caputo, Marchaud…

The authors recently introduced so-called Vandermonde nets. These digital nets share properties with the well-known polynomial lattices. For example, both can be constructed via component-by-component search algorithms. A striking…

Number Theory · Mathematics 2013-11-25 Roswitha Hofer , Harald Niederreiter

The generalised Gegenbauer functions of fractional degree (GGF-Fs), denoted by ${}^{r\!}G^{(\lambda)}_\nu(x)$ (right GGF-Fs) and ${}^{l}G^{(\lambda)}_\nu(x)$ (left GGF-Fs) with $x\in (-1,1),$ $\lambda>-1/2$ and real $\nu\ge 0,$ are special…

Numerical Analysis · Mathematics 2020-06-02 Wenjie Liu , Li-Lian Wang

A generalized matrix function is a generalization of determinant and permanent function. In this paper, we introduced the formula for the value of a generalized matrix function of a linear sum of permutation matrices. We show that a linear…

Rings and Algebras · Mathematics 2019-06-11 Ratsiri Sanguanwong , Kijti Rodtes

We generalize generating functions for hypergeometric orthogonal polynomials, namely Jacobi, Gegenbauer, Laguerre, and Wilson polynomials. These generalizations of generating functions are accomplished through series rearrangement using…

Classical Analysis and ODEs · Mathematics 2013-02-12 Howard S. Cohl , Connor MacKenzie , Hans Volkmer

We prove upper and lower bounds for certain sums of products of fractional parts by using majoring and minorizing functions from Fourier analysis. In special cases the upper bounds are sharp if there exist counterexamples to the Littlewood…

Number Theory · Mathematics 2013-09-09 Thai Hoang Le , Jeffrey D. Vaaler

The aim of this paper is to construct generating functions for some families of special finite sums with the aid of the Newton-Mercator series, hypergeometric series, and $p$-adic integral (the Volkenborn integral). By using these…

Number Theory · Mathematics 2023-02-22 Yilmaz Simsek

Higher order derivatives of functions are structured high dimensional objects which lend themselves to many alternative representations, with the most popular being multi-index, matrix and tensor representations. The choice between them…

Classical Analysis and ODEs · Mathematics 2021-12-01 José E. Chacón , Tarn Duong

This paper presents a novel method for analytical derivations of marginal densities using the fractional derivatives of moment-generating functions. Although the method requires likelihood functions to take specific forms, its assumptions…

Methodology · Statistics 2026-04-06 Si-Yang Li , David A. van Dyk , Maximilian Autenrieth

We develop a general, functional calculus approach to approximation of $C_0$-semigroups on Banach spaces by bounded completely monotone functions of their generators. The approach comprises most of well-known approximation formulas, yields…

Functional Analysis · Mathematics 2018-07-10 A. Gomilko , S. Kosowicz , Yu. Tomilov

The aim of this paper is to study the characteristics of a general method to produce a new approximation sequence from a given one, by using suitable convex combinations.

Functional Analysis · Mathematics 2007-05-23 Lorenzo D'Ambrosio , Elisabetta Mangino

Generalized matrix-fractional (GMF) functions are a class of matrix support functions introduced by Burke and Hoheisel as a tool for unifying a range of seemingly divergent matrix optimization problems associated with inverse problems,…

Optimization and Control · Mathematics 2017-03-07 James V. Burke , Yuan Gao , Tim Hoheisel

A fast approximation to the Boys functions (related to the lower incomplete gamma function of half-integer parameter) by a single closed-form analytical expression for all argument values have been developed and tested. Besides the…

Numerical Analysis · Mathematics 2025-07-09 Dimitri N. Laikov

Generalized Macdonald polynomials (GMP) are eigenfunctions of specifically-deformed Ruijsenaars Hamiltonians and are built as triangular polylinear combinations of Macdonald polynomials. They are orthogonal with respect to a modified scalar…

High Energy Physics - Theory · Physics 2020-01-28 A. Mironov , A. Morozov

The method of self-similar factor approximants is completed by defining the approximants of odd orders, constructed from the power series with the largest term of an odd power. It is shown that the method provides good approximations for…

Mathematical Physics · Physics 2009-11-13 V. I. Yukalov , E. P. Yukalova

We present theory for general partial derivatives of matrix functions on the form $f(A(x))$ where $A(x)$ is a matrix path of several variables ($x=(x_1,\dots,x_j)$). Building on results by Mathias [SIAM J. Matrix Anal. Appl., 17 (1996), pp.…

Numerical Analysis · Mathematics 2023-06-29 Emanuel H. Rubensson

The article studies a class of generalized factorial functions and symbolic product sequences through Jacobi type continued fractions (J-fractions) that formally enumerate the divergent ordinary generating functions of these sequences. The…

Combinatorics · Mathematics 2017-04-26 Maxie D. Schmidt

In this paper, we consider spectral approximation of fractional differential equations (FDEs). A main ingredient of our approach is to define a new class of generalized Jacobi functions (GJFs), which is intrinsically related to fractional…

Numerical Analysis · Mathematics 2014-08-01 Sheng Chen , Jie Shen , Li-Lian Wang