作为结果，算法具有全局和超线性收敛性。
As a result, the proposed algorithm has global and superlinear convergence.
本文给出一种线性收敛的线性方程组迭代解法。
In this paper an iterative solution with linear convergence rate is presented for linear system.
本文还讨论了特殊情况下算法的超线性收敛性。
The superlinear convergence for some special cases is also discussed.
证明了方法的局部收敛性和局部超线性收敛性。
Local convergence and local superlinear convergence rate are proved.
另外在较弱的条件下，证明该方法具有超线性收敛性。
We also prove that the method has superlinear convergence rate under some mild conditions.
一些温和的条件下证明了全局收敛性和线性收敛速率。
The global convergence and linear convergence rate are proved under some mild conditions.
证明该算法在目标函数为一致凸时具有局部超线性收敛性。
It was proved that, when the objective function was uniformly convex, this algorithm possessed superlinear convergence.
在误差界假设条件下，我们得到了改进算法的线性收敛速度。
Furthermore, by using an error bound condition, we establish linear convergence of the proposed algorithm.
在一般假设条件下，证明了算法的全局收敛性和超线性收敛性。
Under the general assumption, the algorithm of global convergence and superlinear convergence are proved.
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。
We prove that the method possesses the global and superlinear convergence under suitable conditions.
在一定的假设条件下，证明了该算法的全局收敛性和超线性收敛。
Under some conditions, the global convergence and the super-linear convergence are proven.
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。
By means of analysing the global error bound, we prove that the method has a R-linear convergence rate.
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。
The global convergence and local superlinear convergence of the method are established by introducing new approximation techniques.
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。
Under mild conditions, we establish the global and superlinear convergence results for the method.
在适当的条件下，比较新颖的证明了算法的全局收敛性及超线性收敛性。
The global convergence and superlinear convergence results of algorithm are novel proved under proper conditions.
证明了此方法的全局收敛性，并给出了它在一定条件下的超线性收敛的结果。
The global convergence results are given for the nonmonotonic trust region technique. Furthermore, the proposed algorithm is superlinearly convergent under a certain growth condition.
我们证明了算法的全局收敛性，并且还在一定条件下证明了算法的Q -线性收敛性。
It has been shown that the algorithms are globally convergent and, under some mild conditions, they are convergent Q-linearly.
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。
Under mild assumptions without the strict complementarity, it is shown that the proposed algorithm enjoys the properties of global and superlinear convergence.
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。
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.
详细分析和论证两个模型的局部超线性收敛性及二次收敛性条件，其中并不需要严格互补条件。
The local superlinear and quadratic convergence of this two models under some mild conditions without the strict complementary condition are analysed and proved.
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。
A new nonmonotonic trust region method is given in this paper. And its global convergence and superlinear convergence are proved. Numerical results are given.
此外我们还将此类算法和一些常见算法做出比较，证明了该类算法在条件稍强的情况下具有线性收敛率。
In addition, we have made a comparison between our methods and other usual ones and finally prove that these methods possess a linear convergence rate under comparatively strong conditions.
在目标函数为一致凸函数的假设条件下，证明了LRKOPT方法的具有全局收敛和局部超线性收敛性。
Under the assumption condition of taking target function as an uniform convex function. We have proved that the LRKOPT has the global convergence and partial superlinear convergence.
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。
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.
本文将集中讨论局部收敛性，特别是证明了在使用DFP或PSB等矩阵校正公式时，修正后的方法在一定的条件下是超线性收敛的。
Particularly, it is proved that if DFP or PSB matrix updating formulae are used, then our method will be convergent superlinearly under some conditions.
利用一个修正的BFGS公式，提出了结合线搜索技术的BFGS -信赖域方法，并在一定条件下证明了该方法的全局收敛性和超线性收敛性。
By using a modified BFGS formula, a BFGS-type trust region method with line search technique for unconstrained optimization problems is proposed.
通过对基于简化线性和非线性模型的自适应控制器的仿真研究，结果表明后者具有更好的收敛性。
Adaptive controllers based on simplified linear and nonlinear models are studied by simulation and the results show that the latter has better property of convergence.
在标准粒子群算法中引入非线性变化权重和变异操作来保证全局收敛并提高收敛精度。
By introducing the nonlinear variation weight and mutational operation into the standard particle swarm algorithm to ensuring the overall convergence and enhance the accuracy of convergence.
计算结果表明，广义协调元对于求解结构几何非线性问题同样具有精度高、收敛快等优点。
Numerical results indicate that the generalized conforming element has the advantages of high accuracy and uniform convergence to geometrically nonlinear problem of structures.
计算结果表明，广义协调元对于求解结构几何非线性问题同样具有精度高、收敛快等优点。
Numerical results indicate that the generalized conforming element has the advantages of high accuracy and uniform convergence to geometrically nonlinear problem of structures.
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