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

被引：31
|
作者：
Feng, Dexiang [1 ,2 ]
Sun, Min [3 ]
Wang, Xueyong [3 ]
机构：
[1] Fudan Univ, Sch Management Sci, Shanghai, Peoples R China
[2] Qufu Normal Univ, Qufu 276826, Shandong, Peoples R China
[3] Qufu Normal Univ, Sch Management, Qufu 276826, Shandong, Peoples R China
来源：
JOURNAL OF INEQUALITIES AND APPLICATIONS | 2017年
关键词：
nonlinear equations; conjugate gradient method; projection method; global convergence; MONOTONE EQUATIONS; CONVEX CONSTRAINTS; PROJECTION METHOD; CONVERGENCE; OPTIMIZATION; ALGORITHM;
D O I：
10.1186/s13660-017-1510-0
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.
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页数：8
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