On the accurate computation of the Newton form of the Lagrange interpolant

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED Numerical Algorithms Pub Date : 2024-05-01 DOI:10.1007/s11075-024-01843-7
Y. Khiar, E. Mainar, E. Royo-Amondarain, B. Rubio
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Abstract

In recent years many efforts have been devoted to finding bidiagonal factorizations of nonsingular totally positive matrices, since their accurate computation allows to numerically solve several important algebraic problems with great precision, even for large ill-conditioned matrices. In this framework, the present work provides the factorization of the collocation matrices of Newton bases—of relevance when considering the Lagrange interpolation problem—together with an algorithm that allows to numerically compute it to high relative accuracy. This further allows to determine the coefficients of the interpolating polynomial and to compute the singular values and the inverse of the collocation matrix. Conditions that guarantee high relative accuracy for these methods and, in the former case, for the classical recursion formula of divided differences, are determined. Numerical errors due to imprecise computer arithmetic or perturbed input data in the computation of the factorization are analyzed. Finally, numerical experiments illustrate the accuracy and effectiveness of the proposed methods with several algebraic problems, in stark contrast with traditional approaches.

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论拉格朗日插值法牛顿形式的精确计算
近年来,许多人致力于寻找非对角全正矩阵的对角因式分解,因为精确计算这些因式分解可以非常精确地数值求解几个重要的代数问题,即使是对大型非条件矩阵也是如此。在此框架下,本研究提供了牛顿基拼合矩阵的因式分解--在考虑拉格朗日插值问题时,这种因式分解具有重要意义--同时还提供了一种算法,能够以较高的相对精度进行数值计算。这样就能进一步确定插值多项式的系数,并计算奇异值和配位矩阵的逆。确定了保证这些方法高相对精度的条件,以及在前一种情况下,保证除法差分经典递推公式高相对精度的条件。分析了因式分解计算中由于计算机运算不精确或输入数据扰动而导致的数值误差。最后,通过数值实验说明了所提方法在几个代数问题上的准确性和有效性,与传统方法形成了鲜明对比。
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来源期刊
Numerical Algorithms
Numerical Algorithms 数学-应用数学
CiteScore
4.00
自引率
9.50%
发文量
201
审稿时长
9 months
期刊介绍: The journal Numerical Algorithms is devoted to numerical algorithms. It publishes original and review papers on all the aspects of numerical algorithms: new algorithms, theoretical results, implementation, numerical stability, complexity, parallel computing, subroutines, and applications. Papers on computer algebra related to obtaining numerical results will also be considered. It is intended to publish only high quality papers containing material not published elsewhere.
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