On the Computation of Recurrence Coefficients for Univariate Orthogonal Polynomials

被引:4
|
作者
Liu, Zexin [1 ,2 ]
Narayan, Akil [1 ,2 ]
机构
[1] Univ Utah, Dept Math, Salt Lake City, UT 84112 USA
[2] Univ Utah, Sci Comp & Imaging SCI Inst, Salt Lake City, UT 84112 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Orthogonal polynomials; Recurrence coefficients; GAUSSIAN QUADRATURE; APPROXIMATION; CHAOS;
D O I
10.1007/s10915-021-01586-w
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Associated to a finite measure on the real line with finite moments are recurrence coefficients in a three-term formula for orthogonal polynomials with respect to this measure. These recurrence coefficients are frequently inputs to modern computational tools that facilitate evaluation and manipulation of polynomials with respect to the measure, and such tasks are foundational in numerical approximation and quadrature. Although the recurrence coefficients for classical measures are known explicitly, those for nonclassical measures must typically be numerically computed. We survey and review existing approaches for computing these recurrence coefficients for univariate orthogonal polynomial families and propose a novel "predictor-corrector" algorithm for a general class of continuous measures. We combine the predictor-corrector scheme with a stabilized Lanczos procedure for a new hybrid algorithm that computes recurrence coefficients for a fairly wide class of measures that can have both continuous and discrete parts. We evaluate the new algorithms against existing methods in terms of accuracy and efficiency.
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页数:26
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