A family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations

A family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations
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用于大规模非线性方程组的一系列无导数共轭梯度方法

DOI:
10.1016/j.cam.2008.03.050
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发表时间:
2009-02
影响因子:
2.4
通讯作者:
Qing-Jie Hu
Qing-Jie Hu
中科院分区:
数学2区
文献类型:
--
作者:
Yunhai Xiao;Wanyou Cheng;Qing-Jie Hu

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本文给出了求解大规模非线性方程组的一族无导数共轭梯度法。它们来自两个修正的共轭梯度法[W.Y. Cheng,一种基于两项PRP的下降法,数值模拟.功能anal.最佳。28(2007)第1217 - 1230段;张伟杰,周德辉。李明,一种改进的共轭梯度法及其全局收敛性,中国科学院学报,2002。anal. 26(2006)629 - 640]最近提出了用于无约束优化问题的算法。在适当的条件下,证明了该方法的全局收敛性.数值实验表明,此方法是有效的。
In this paper, we propose a family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations. They come from two modified conjugate gradient methods [W.Y. Cheng, A two term PRP based descent Method, Numer. Funct. Anal. Optim. 28 (2007) 1217–1230; L. Zhang, W.J. Zhou, D.H. Li, A descent modified Polak–Ribiére–Polyak conjugate gradient method and its global convergence, IMA J. Numer. Anal. 26 (2006) 629–640] recently proposed for unconstrained optimization problems. Under appropriate conditions, the global convergence of the proposed method is established. Preliminary numerical results show that the proposed method is promising.
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