%0 Journal Article
%T 求解无约束问题的修正PRP共轭梯度算法<br>A Modified Polak-Ribière-Polyak Conjugate Gradient Algorithm for Smooth Convex Programs
%A 李春念
%A 袁功林&lt
%A br&gt
%A LI Chun-nian
%A YUAN Gong-lin
%J 西南大学学报(自然科学版)
%D 2018
%R 10.13718/j.cnki.xdzk.2018.09.011
%X 提出了一种改进的PRP共轭梯度算法，其搜索方向自动具有充分下降性和信赖域性质，且在一定条件下，具有全局收敛性.数值结果表明该算法对求解无约束光滑问题是有效的.<br>In this paper, a modified PRP conjugate gradient algorithm is proposed. The search direction of this algorithm belongs to a trust region automatically, and its search direction possesses descent property. Under suitable conditions, the method owns global convergence. Some elementary numerical experiments indicate that the presented method is effective for unconstrained smooth problems
%K 共轭梯度法
%K 下降性
%K 全局收敛性&lt
%K br&gt
%K conjugate gradient algorithm
%K descent property
%K global convergence
%U http://xbgjxt.swu.edu.cn/jsuns/html/jsuns/2018/9/20180911.htm