一类线性系统的Orthomin(k)收敛速率的尖锐估计

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED
Andrei Drăgănescu , Florin Spinu
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引用次数: 0

摘要

在这项工作中,我们证明了Orthomin(k)的收敛速率适用于形式为(I+ρU)x=b的系统,其中U是一个酉算子,0<ρ<;1小于或等于ρ。此外,我们还给出了算子U和ρ>;0的例子,其中Orthomin(k)的渐近收敛速率正好是ρ,从而表明估计是尖锐的。虽然被审查的系统本身可能不太感兴趣,但它们的存在表明,一般来说,Orthomin(k)并不比Orthomin(1)收敛得快。进一步,我们给出了在k≥2时,Orthomin(k)与Orthomin(2)具有相同的渐近收敛速率,但小于Orthomin(1)的系统的例子。后一类系统与某些偏微分方程的数值解有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sharp estimates for the convergence rate of Orthomin(k) for a class of linear systems
In this work we show that the convergence rate of Orthomin(k) applied to systems of the form (I+ρU)x=b, where U is a unitary operator and 0<ρ<1, is less than or equal to ρ. Moreover, we give examples of operators U and ρ>0 for which the asymptotic convergence rate of Orthomin(k) is exactly ρ, thus showing that the estimate is sharp. While the systems under scrutiny may not be of great interest in themselves, their existence shows that, in general, Orthomin(k) does not converge faster than Orthomin(1). Furthermore, we give examples of systems for which Orthomin(k) has the same asymptotic convergence rate as Orthomin(2) for k2, but smaller than that of Orthomin(1). The latter systems are related to the numerical solution of certain partial differential equations.
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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