Orthogonal polynomial expansions on sparse grids

被引:2
|
作者
Cao, Yanzhao [1 ,2 ]
Jiang, Ying [2 ]
Xu, Yuesheng [2 ,3 ]
机构
[1] Auburn Univ, Dept Math & Stat, Auburn, AL 36830 USA
[2] Sun Yat Sen Univ, Sch Math & Computat Sci, Guangdong Prov Key Lab Computat Sci, Guangzhou 510275, Guangdong, Peoples R China
[3] Syracuse Univ, Dept Math, Syracuse, NY 13244 USA
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Orthogonal polynomial; Sparse grid; Spectral method; Collocation method; FAST ALGORITHMS; INTERPOLATION; TRANSFORMS;
D O I
10.1016/j.jco.2014.04.001
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We study the orthogonal polynomial expansion on sparse grids for a function of d variables in a weighted L-2 space. Two fast algorithms are developed for computing the orthogonal polynomial expansion and evaluating a linear combination of orthogonal polynomials on sparse grids by combining the fast cosine transform, the fast transforms between the qChebyshev orthogonal polynomial basis and the orthogonal polynomial basis for the weighted L2 space, and a fast algorithm of computing hierarchically structured basis functions. The total number of arithmetic operations used in both algorithms is O(n log(d+1) n) where n is the highest polynomial degree in one dimension. The exponential convergence of the approximation for the analytic function is investigated. Specifically, we show the sub-exponential convergence for analytic functions and moreover we prove the approximation order is optimal for the Chebyshev orthogonal polynomial expansion. We furthermore establish the fully exponential convergence for functions with a somewhat stronger analytic assumption. Numerical experiments confirm the theoretical results and demonstrate the efficiency and stability of the proposed algorithms. (C) 2014 Elsevier Inc. All rights reserved.
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页码:683 / 715
页数:33
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