GLOBAL CONVERGENCE PROPERTIES OF CONJUGATE GRADIENT METHODS FOR OPTIMIZATION
GLOBAL CONVERGENCE PROPERTIES OF CONJUGATE GRADIENT METHODS FOR OPTIMIZATION
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DOI：
10.1137/0802003
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发表时间：
1992-02-01
影响因子：
3.1
通讯作者：
Nocedal, Jorge
中科院分区：
文献类型：
--
作者：
Gilbert, Jean Charles;Nocedal, Jorge
本文研究了无重启的非线性共轭梯度法在实际线搜索下的收敛性。分析涵盖了两类方法是全局收敛的光滑，非凸函数。Fletcher-Reeves方法的一些性质在第一类方法中起着重要的作用，而第二类方法与Polak-Ribiere方法共享一个重要的性质。数值实验。
This paper explores the convergence of nonlinear conjugate gradient methods without restarts, and with practical line searches. The analysis covers two classes of methods that are globally convergent on smooth, nonconvex functions. Some properties of the Fletcher-Reeves method play an important role in the first family, whereas the second family shares an important property with the Polak-Ribiere method. Numerical experiments are presented.