下降的非线性共轭梯度法及其全局收敛性

共轭梯度法是解决大规模无约束优化问题的一种重要方法．文中给出了两种下降的非线性共轭梯度法，并在标准的Wolfe准则下证明了其全局收敛性．数值实验表明这两种方法在所给的例子中是有效可行的．

Convergence of the descent nonlinear conjugate gradient methods

Conjugate gradient methods are typically used to solve large scale unconstrained optimization problems. Two descent conjugate gradient methods are proposed,and the global convergence with standard Wolfe conditions is proved. The numerical results show that the methods are efficient for the given test problems.