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New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization

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成果类型:
期刊论文
作者:
Zhang, Li*
通讯作者:
Zhang, Li
作者机构:
[Zhang, Li; Zhang, L] Changsha Univ Sci & Technol, Coll Math & Computat Sci, Changsha 410076, Hunan, Peoples R China.
通讯机构:
[Zhang, Li] C
Changsha Univ Sci & Technol, Coll Math & Computat Sci, Changsha 410076, Hunan, Peoples R China.
语种:
英文
关键词:
HS method;descent direction;global convergence
期刊:
Computational and Applied Mathematics
ISSN:
2238-3603
年:
2009
卷:
28
期:
1
页码:
111-133
基金类别:
NSF foundation of China [10701018]
机构署名:
本校为第一且通讯机构
院系归属:
数学与统计学院
摘要:
Based on the secant condition often satisfied by quasi-Newton methods, two new versions of the Hestenes-Stiefel (HS) nonlinear conjugate gradient method are proposed, which are descent methods even with inexact line searches. The search directions of the proposed methods have the form dk = -θkgk + βHSk dk-1, or dk = -gk + βHSk dk-1 + θkyk-1. When exact line searches are used, the proposed methods reduce to the standard HS method. Convergence properties of the proposed methods are discussed. These results are also extended to some other conj...

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