A Gauss–Newton-like conjugate gradient method for large-scale nonlinear equations and image restoration problems

IF 2.8 2区 数学 Q1 MATHEMATICS, APPLIED
Zhan Wang, Shengjie Li
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引用次数: 0

Abstract

In this paper, we present a Gauss–Newton-like conjugate gradient method for solving large-scale nonlinear equations. This new method can essentially be regarded as a spectral three-term conjugate gradient method, where the spectral parameter is designed based on an approximate Gauss–Newton direction and the secant equation. Global convergence is established under appropriate conditions. Numerical experiments demonstrate that the presented method is more effective than other existing methods in solving large-scale nonlinear equations. Moreover, this new method exhibits significant advantages in image restoration problems.
大尺度非线性方程和图像恢复问题的类高斯-牛顿共轭梯度法
本文给出了求解大型非线性方程的一类高斯-牛顿共轭梯度法。该方法本质上可以看作是一种频谱三项共轭梯度法,其中频谱参数是基于近似的高斯-牛顿方向和割线方程设计的。在适当的条件下,建立了全局收敛性。数值实验表明,该方法在求解大规模非线性方程时比现有方法更有效。此外,该方法在图像恢复问题上具有显著的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied Mathematics Letters
Applied Mathematics Letters 数学-应用数学
CiteScore
7.70
自引率
5.40%
发文量
347
审稿时长
10 days
期刊介绍: The purpose of Applied Mathematics Letters is to provide a means of rapid publication for important but brief applied mathematical papers. The brief descriptions of any work involving a novel application or utilization of mathematics, or a development in the methodology of applied mathematics is a potential contribution for this journal. This journal''s focus is on applied mathematics topics based on differential equations and linear algebra. Priority will be given to submissions that are likely to appeal to a wide audience.
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