论文标题
混合riemannian共轭梯度方法具有全球收敛性能
Hybrid Riemannian Conjugate Gradient Methods with Global Convergence Properties
论文作者
论文摘要
本文介绍了新的Riemannian共轭梯度方法和在强沃尔夫条件下的全球收敛分析。新方法的主要思想是将Dai-Yuan方法的良好全局收敛属性与Hestenes-Stiefel方法的有效数值性能相结合。所提出的方法与单位球体上瑞利商的最小化问题的现有方法进行了很好的比较。数值比较表明它们的性能比现有的表现更好。
This paper presents new Riemannian conjugate gradient methods and global convergence analyses under the strong Wolfe conditions. The main idea of the new methods is to combine the good global convergence properties of the Dai-Yuan method with the efficient numerical performance of the Hestenes-Stiefel method. The proposed methods compare well numerically with the existing methods for the Rayleigh quotient minimization problem on the unit sphere. Numerical comparisons show that they perform better than the existing ones.
