如果您没有使用某种超全局变量（比如环境变量），您可以安全地删除它们来获得一点加速，从而避免在每一个请求上解析它们。
If you aren't using certain superglobals (such as environment variables), you can safely remove them to gain a small speedup from not having to parse them on every request.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
提出复合非光滑优化问题的一类算法，并证明这种算法保持全局收敛性且敛速达到超线性。
This paper discusses a model algorithm for composite nonsmooth optimization problems and proves that the algorithm holds global convergence and in the meantime the convergent rate is superlinear.
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.
最后，将全局脸图像和局部细节信息相结合，得到最终的人脸超分辨率结果。
Finally, the global face image and local details are combined to the final face super-resolution results.
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.
基于此超结构，建立了全局能量集成的混合整数非线性规划模型，并用列队竞争算法进行求解。
Based on the super structure, a mixed integer non-linear programming (MINLP) model is established for total site energy integration.
基于此超结构，建立了全局能量集成的混合整数非线性规划模型，并用列队竞争算法进行求解。
Based on the super structure, a mixed integer non-linear programming (MINLP) model is established for total site energy integration.
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