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global convergence相关的网络例句

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与 global convergence 相关的网络例句 [注:此内容来源于网络,仅供参考]

By the way, we describe the modified quasi-Newton algorithm used the line search , and have given its global convergence and superlinear convergence.

接下来描述了采用线性搜索的修正拟Newton算法,并给出了它的全局收敛性与超线性收敛性。

Furthermore, the global convergence and superlinear convergence rate are proved under mild assumptions without the strict complementarity.

此外,在不需要严格互补的温和条件下,我们证明了算法的全局收敛性和超线性收敛性。

The algorithm is the combination of the method with global convergence and thatwith locally superlinear convergence.

其特点之一是该方法在每步迭代中只需要计算一个或三个具有相同系数矩阵的线性方程组。

Since a new generalized projection technique is contained in the auxiliary direction formula, under some mild assumptions without the strict complementarity, the global convergence and superlinear convergence of the algorithm can be obtained.

由于一种新的广义投影技术包含在辅助方向的计算公式中,因而在无严格互补等较温和的假设下便可得到算法的全局收敛性及超线性收敛性。

LC1 unconstrained optimization problem was discussed in the second chapter, giving a new trust region method and proving its global convergence and superlinear convergence under some mild conditions .

第二章讨论了LC~1无约束优化问题。给出了一个新的信赖域算法,并在一定的条件下证明了算法的全局收敛性和局部超线性收敛性。

To solve it, we turn it into nonsmooth equations, utilizing inexact theory we give an inexact generalized Newtons method and under some mild conditions we prove that it is global convergence and superlinear convergence .

首先将其约束问题的求解转化为非光滑方程组的求解,然后利用不完全求解理论给出了一个非精确的广义牛顿算法,在一定的条件下证明了算法的全局收敛性和局部超线性收敛性并给出了LC~1非线性约束问题的收敛性条件。

We also introduce a control function, prove the global convergence, and prove the local superlinear convergence under some conditions. Then we propose another new algorithm by using an existed approximation functions, which has the same characters as the first algorithms does. Finally, the result of the numerical experiments indicates the efficiency of the first algorithm. The paper contains four parts.

本文还引入了新的控制函数,并证明了算法具有全局收敛性和在一定的条件下具有局部超线性收敛性;然后,在第一个算法的基础上,本文利用已有的光滑逼近函数提出了另外一个新的算法,通过适当参数选取,证明了新的算法具有与第一个算法同样良好的收敛性质;最后,通过数值计算说明了算法的高效性。

In Chapter 3, we propose two new quasi-Newton type trust region methods for solving unconstrained optimization problems. These algorithms combine two types of the preconvex part of modified Broydens family proposed in chapter 1 with trust region algorithm effectively, they have global convergence property and superlinear convergence rate.

第三章,给出了用来求解无约束最优化问题两种新的拟牛顿信赖域算法,这些算法将第一章给出的两种修改Broyden非凸族与信赖域算法有效结合起来,它们具有全局收敛性和超线性收敛速度。

Which possesses global convergence and locally superlinear convergence proven without strict complementarity at the Danskin point.

在不假设在Danskin点处满足严格互补条件的情况下证明了算法具有超线性收敛速度及全局收敛的性质。

Simulation results show that the algorithm has better global convergence ability and rapider convergence velocity through optimization tests of benchmark functions.

通过标准函数的优化试验,仿真结果表明该算法有较强的全局收敛能力和较快的收敛速度。

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