Document Type
Article
Publication Date
1-1-2003
Abstract
Let μ be a probability measure on the real line with finite moments of all orders. Apply the Gram-Schmidt orthogonalization process to the system {1, x, x2, . . ., xn, . . .} to get orthogonal polynomials Pn(x), n ≥ 0, which have leading coefficient 1 and satisfy (x-αn)Pn(x) = Pn+1(x) +ωnPn-1(x). In general it is almost impossible to use this process to compute the explicit form of these polynomials. In this paper we use the multiplicative renormalization to develop a new method for deriving generating functions for a large class of probability measures. From a generating function for n we can compute the orthogonal polynomials P n(x), n ≥ 0. Our method can be applied to derive many classical polynomials such as Hermite, Charlier, Laguerre, Legendre, Chebyshev (first and second kinds), and Gegenbauer polynomials. It can also be applied to measures such as geometric distribution to produce new orthogonal polynomials.
Publication Source (Journal or Book title)
Taiwanese Journal of Mathematics
First Page
89
Last Page
101
Recommended Citation
Asai, N., Kubo, I., & Kuo, H. (2003). Multiplicative renormalization and generating functions I. Taiwanese Journal of Mathematics, 7 (1), 89-101. https://doi.org/10.11650/twjm/1500407519