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uniformly相关的网络例句

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与 uniformly 相关的网络例句 [注:此内容来源于网络,仅供参考]

The results of simulation show the new algorithm is uniformly convergent and robustness.

该算法具有强一致收敛性和较强的鲁棒性。

Then,the uniformly convergent rate of any order sample cyclic-moments of cyclostationary processes is obtained.

本文从循环平衡的观点出发来研究乘性和加性噪声中的谐波恢复问题。

Then, which of the convergent plate elements are convergent uniformly with respect to the parameter ε?

那么,哪些板元对奇异摄动问题关于参数ε是一致收敛的哪?

Moreover, classical multigrid methods, such as W-cycle and Variable V-cycle, are shown to be convergent uniformly for this mortar type TRUNC element.

我们还用经典多重网格方法(可变的V-循环、W-循环)求解带mortar条件的TRUNC元解,证明所构造的网格转移算子满足收敛性条件,从而传统多重网格方法作预处理的条件数为一致有界。

The existence of pointwise robust convergent algorithm and uniformly robust convergence is next investigated. We propose an optimal l〓 robustness synthesis method for structured perturbations system by taking advantage of the famous Small Gain Theorem.

证明了最优l〓辨识算法的存在性;证明了黑箱辨识存在辨识算法使全局误差收敛于有界区间;提出并证明了逐点鲁棒收敛算法的存在性;证明了一致鲁棒收敛算法的存在性。

In this paper, the problem of an iterative sequence approximation a common fixed point for nonexpansive non-self mappings is studied in real uniformly convex Banach space, then we obtain a strongly convergence theorem.

在实一致凸Banach空间中,讨论了关于非扩张非自映射序列逼近公共不动点的问题,获得了一个强收敛定理,改进和推广了现有文献的一些相应结果。

The objective of Chapter 2 is to give the weak convergence theorem of S ={T1 :t E G of asymptotically nonexpansive mappings in a uniformly convex Banach space without assuming that X has a Frechet differentiable norm.

本文第二章在G仅要求是一个定向网,X为不具有范数Frechet可微条件的一致凸Banach空间的情况下,给出了一族渐近非扩张映射的弱收敛定理。

A class of modified BFGS algorithm which satisfies the new quasi-Newton equation is proposed in the paper[1],and the global convergence of the algorithm is proved under the condition that the objective function is uniformly convex.

文献[1]曾在已建立的一类新拟牛顿方程 Bk+1sk=yk-=yk+kγskTsksk的基础上,证明了满足新拟牛顿方程的一类改进BFGS算法在目标函数为一致凸的条件下,具有全局收敛性。

In this paper,several quasi-Newton algorithms are generalized to a class of new quasi-Newton equation,several modified quasi-Newton algorithm s are obtained and their global convergence are proved under the objective function is uniformly convex.

将几个拟牛顿算法推广到一类新拟牛顿方程,得到几个修正拟牛顿算法;在目标函数为一致凸的条件下,证明了它们都具有全局收敛性。

Under certain conditions, we prove the global convergence of the modified Broydens class of quasi-Newton methods for solving uniformly convex minimization problems.

并证明算法用于求解一致凸函数极小化问题时的全局收敛性。

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