An approximate gradient-type method for nonlinear symmetric equations with convex constraints-Reference-Cited by-同舟云学术

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An approximate gradient-type method for nonlinear symmetric equations with convex constraints

Published:2023-10 Issue: Volume:431 Page:115259
ISSN:0377-0427
Container-title:Journal of Computational and Applied Mathematics
language:en
Short-container-title:Journal of Computational and Applied Mathematics

Author:

Liu Jinkui,Zhang Ning,Wang Jing,Lu Zuliang

Funder

Chongqing Research Program of Basic Research and Frontier Technology

Chongqing Three Gorges University

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference21 articles.

1. A globally and superlinearly convergent Gauss–Newton-based BFGS method for symmetric nonlinear equations;Li;SIAM J. Numer. Anal.,1999

2. Norm descent conjugate gradient methods for solving symmetric nonlinear equations;Xiao;J. Global Optim.,2015

3. A nonlinear conjugate gradient algorithm with an optimal property and an improved wolfe line search;Dai;SIAM J. Optim.,2013

4. New three-term conjugate gradient method with guaranteed global convergence;Liu;Int. J. Comput. Math.,2014

5. A norm descent derivative-free algorithm for solving large-scale nonlinear symmetric equations;Liu;J. Comput. Appl. Math.,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A new approximate descent derivative-free algorithm for large-scale nonlinear symmetric equations;Computational and Applied Mathematics;2024-08-20

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