نتایج جستجو برای: generalized laguerre polynomials

تعداد نتایج: 202447  

Journal: :Proceedings of the American Mathematical Society 1991

Journal: :Journal of Nonlinear Mathematical Physics 2021

2007
Paul Barry

We introduce a family of number triangles defined by exponential Riordan arrays, which generalize Pascal’s triangle. We characterize the row sums and central coefficients of these triangles, and define and study a set of generalized Catalan numbers. We establish links to the Hermite, Laguerre and Bessel polynomials, as well as links to the Narayana and Lah numbers.

Journal: :Appl. Math. Lett. 2003
Hari M. Srivastava Harry A. Mavromatis Rajai S. Alassar

Motivated essentially by their possible need in a fairly large number of physical and chemical contexts, Mavromatis and Alsssar [l] derived several associated Laguerre integral results by eliminating au unnecessary constraint used in an earlier paper on the subject by Mavromatis [2]. The main object of the present sequel to these recent works is to investigate and apply much more general famili...

1989
Ira M. Gessel IRA M. GESSEL

We consider several generalizations of rook polynomials. In particular we develop analogs of the theory of rook polynomials that are related to general Laguerre and Charlier polynomials in the same way that ordinary rook polynomials are related to simple Laguerre polynomials.

Journal: :Journal of Approximation Theory 2011
Manuel Alfaro Juan J. Moreno-Balcázar Ana Peña M. Luisa Rezola

This paper deals with Mehler-Heine type asymptotic formulas for so called discrete Sobolev orthogonal polynomials whose continuous part is given by Laguerre and generalized Hermite measures. We use a new approach which allows to solve the problem when the discrete part contains an arbitrary (finite) number of mass points. 2000MSC: 42C05, 33C45.

2014
Ashraf Afifi

Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient properties that other methods hardly provide. However the performance of SVMs is very sensitive to how the kernel function is selected, the challenge is to choose the kernel function for accurate data classification. I...

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