摘要
In this paper, a conjugate-gradient method of invariancy to nonlinear scaling with respect to a conic function is proposed. This method may be used in the minimizer of a larger class of functions in a finite number of iterations, and this class of functions is more general than class of functions using the conjugate-gradient method of a conic function (to denote simply CCG)[1] to find its minimzer. In fact, this method is the extension of the CCG method. The results of the numerical evaluation show that the new method has a great effect.
In this paper, a conjugate-gradient method of invariancy to nonlinear scaling with respect to a conic function is proposed. This method may be used in the minimizer of a larger class of functions in a finite number of iterations, and this class of functions is more general than class of functions using the conjugate-gradient method of a conic function (to denote simply CCG)[1] to find its minimzer. In fact, this method is the extension of the CCG method. The results of the numerical evaluation show that the new method has a great effect.
出处
《计算数学》
CSCD
北大核心
2001年第1期49-58,共10页
Mathematica Numerica Sinica
关键词
无约束极小问题
圆锥函数
共轭梯度法
函数极小化
非线性尺度不变性
CCG法
unconstrained minimization, conjugate-gradient methods of conic functions, numerical methods, optimization theorems, function minimization
