By means of analysing the global error bound, we prove that the method has a R-linear convergence rate.
借助于全局误差界的分析，证明了所提方法具有R -线性收敛速度。
It is shown that this method possesses global convergence and the penalty parameters are adjusted only finite times under mild conditions.
在较为温和的条件下证明了方法的全局收敛性，及罚参数只需进行有限次调整。
Numerical examples illustrate that the present method possesses both good capability to search global optima and far higher convergence speed than that of chaos optimization method.
算例表明，当混沌搜索的次数达到一定数量时，混合优化方法可以保证算法收敛到全局最优解，且计算效率比混沌优化方法有很大提高。
In this paper we present a smoothing Newton method for solving ball constrained variational inequalities. Global and superlinear convergence theorems of the proposed method are established.
研究球形约束变分不等式求解的算法，提出一种光滑化牛顿方法，证明了该方法具有全局收敛性和超线性收敛。
This paper mainly studies the numerical solution of a class of nonlinear diffusion equations using a monotone iteration method with the global convergence.
本文主要运用一种具有全局收敛性的单调迭代法求解了一类非线性扩散方程的数值解。
The global convergence and local superlinear convergence of the method are established by introducing new approximation techniques.
由于引进了新的逼近技术，该方法具有全局收敛性和局部超线性收敛性。
To improve the learning efficiency and global convergence we present the monotone homotopy method, which has the same convergence as the Newton's method, to train the weights of the network.
为改进网络学习效率及大范围收敛性，提出了网络权值学习的单调同伦方法，该方法具有与牛顿法相同的二阶收敛性。
A new nonmonotonic trust region method is given in this paper. And its global convergence and superlinear convergence are proved. Numerical results are given.
给出一种新的非单调信赖域方法，证明了算法的全局收敛性和超线性收敛性，最后给出了数值结果。
We prove that the method possesses the global and superlinear convergence under suitable conditions.
在适当的条件下我们将证明此方法的全局收敛性和超线性收敛性。
The paper presents a nonlinear conjugate gradient method for unconstrained optimization problem, and proves its global convergence under exact line searches.
该文提出一种无约束优化非线性共轭梯度法，证明了精确线性搜索下的全局收敛性。
The method is simple and practical and has the feature of global convergence.
该方法简单、实用，并且具有全局收敛的特点。
We prove that the algorithm is well defined and the global convergence of method is obtained without regular conditions.
第四章我们首先证明了算法是有定义的，其次在没有正则性条件的假设下证明了算法的全局收敛性。
Chapter 3 constructs a new generalized pattern search method for linear equality constrained optimization problems and gives the proofs of the global convergence.
第3章给出了广义模式搜索算法对线性等式约束最优化问题的一个新解法，并证明了这种算法的全局收敛性。
At the same time, the method of time-varying crossover probability factor was adopted to improve the global searching ability and convergence speed of MDE.
同时，采用时变交叉概率因子的方法以提高算法的全局搜索能力和收敛速率。
This paper presents a wide line search and gives a new conjugate gradient method, with global convergence.
本文对该算法中的线搜索进行了推广，提出了一种新的非线性共轭梯度算法并证明了其全局收敛性。
Genetic Algorithms, as a good optimization method, have features of robustness and global convergence.
基因遗传算法作为一种优化设计方法具有通用性强、稳定性好以及全局收敛等特性。
Pr conjugate gradient method is one of the efficient methods for solving large scale unconstrained optimization problems, however, its global convergence has not been solved for a long time.
PR共轭梯度法是求解大型无约束优化问题的有效算法之一，但是算法的全局收敛性在理论上一直没有得到解决。
Under mild conditions, we establish the global and superlinear convergence results for the method.
在适当的假设条件下，我们证明了算法具有全局收敛性和超线性收敛性。
Based on the steepest descent method and the conjugate gradient method, a hybrid algorithm is proposed in this paper, and its global convergence is proved.
将最速下降法与共轭梯度法有机结合起来，构造出一种混合优化算法，并证明其全局收敛性。
And through compare with non-Evolutionary Map building method, the Evolutionary Reinforcement learning algorithm can increase search map efficiency and expedite convergence speed of global map.
通过与非进化模式下的多机器人地图构建方法的比较，该算法可以提高地图搜索的效率，加快全局地图的收敛。
Underan inexact line search condition and some other mild conditions, the global convergence was established. Preliminary numerical results show that the proposed method is promsing.
在较为温和的条件下，利用宽松的非精确线搜索条件得到全局收敛性结果，同时数值实验表明了算法的有效性。
The numerical example shows the effectiveness and global convergence of the method.
数值实例显示了该方法的高效性与大范围收敛性。
A new method to correct the barral distortion of endoscope image based on the line search method of guaranteed global convergence is presented.
根据内窥镜成像特性以及基于全局收敛的线性搜索法来确定畸变图像中心和多项式系数。
We defined the new quasi-cone condition, established the homotopy equation and proved the global convergence of this homotopy method.
通过对可行域定义新的拟锥条件，给出相应同伦方程，并证明此同伦算法在此拟锥条件下具有全局收敛性。
Under general conditions, the local and global convergence results of the new method are proved. Numerical experiments show that the new method is very efficient.
在通常条件下，证明了全局收敛性及局部超线性收敛结果，数值结果验证了新方法的有效性。
The global and superlinear convergence of the method is obtained under very mild conditions.
在较弱的条件下，证明了算法的全局收敛性。
Under weaker assumptions, we prove the global convergence properties of the method.
在较弱的条件下，我们证明了算法的全局收敛性。
Under weaker assumptions, we prove the global convergence properties of the method.
在较弱的条件下，我们证明了算法的全局收敛性。
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