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rate of convergence相关的网络例句

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

Some authors studied the rate of point-wise rate of convergence, asymptotic formula of Voronovskaja type, and some direct results about these type of operators.

Gupta等给出了有关这类算子点态逼近的速度、 Voronovskaja型渐近公式以及一些正结果。

It usually has a so-called superlinear convergence behavior. The rate of convergence seems to improve as the iteration proceeds. For another say, the rate of residual variable will be improved as we increase its iteration.

GMRES算法在迭代过程中通常表现出一种加速收敛行为,随着迭代次数的增加,这种加速收敛现象越明显,即残量收敛会随着迭代步数的增加而逐渐得到改善。

In the third chapter, we study the approximation and weighted approximation for a kind of generalized Baskakov operators of two-variable. Using different weight functions, we discuss the convergence on weighted space of polynomials and rate of convergence with Jacobi weight for this kind of two-dimensional product-type operators, which extends the results of one-dimensional operators.

第三章研究一类二元广义Baskakov算子的逼近及其加权逼近,主要针对于不同的权函数讨论了这类乘积型的二元算子及其导数在多项式权空间上的收敛性和加Jacobi权的收敛阶,把一元的结果推广到多元的情形。

It is improved to solve the prematurely and stagnation problems of traditional Ant Colony Optimization in the paper. First, mean value method is used to update pheromone to avoid premature convergence which leads to non-globally optimal solution. Second, Pheromone is updated by Best Track to speed the rate of convergence which will help to avoid locally optimal solution.

本文针对基本蚁群算法比较容易陷入早熟和停滞,对现有蚁群算法的信息素更新规则进行了改进,一是采用平均值法更新信息素,避免算法过早收敛于非全局最优解;二是采用最佳路径法更新信息素,可加快收敛速度,并使算法跳出局部最优解。

This article is going to study the convergence and rate of convergence about nonhomogeneous Markov chains.

本文主要研究非齐次马氏链的收敛及收敛速度。

If the pattern has a low rate of convergence, the time of the human and machines will be wasted and the answer are not surely attainable.So,we must look for the patterns with the high rate of convergence or try to settle some parameters of the iteration patterns (for instance the overrelaxation parameter of SOR iterative method).

本文第二章针对AOR迭代法考察了当线性方程组的系数矩阵A为(1,1)相容次序矩阵且其Jacobi特征值为纯虚数或零时的迭代收敛范围,最优参数(即最优松弛因子和最优加速因子)及与之相应的谱半径,并将此最优谱半径与相应的SOR的进行比较,定量的给出在不同条件下,AOR和SOR迭代法各有其优越性,从而圆满的解决了在这两种迭代法之间如何适当的选择最佳迭代法的问题。

They didn't possess strong convergence and quadratic convergence rate,more-over,their convergence properties and rate of convergence were only local.

无强收敛性和二次收敛率,甚至收敛性与收敛速度只是局部的。

Experimental results show that the new algorithm can greatly improve the global convergence ability and enhance the rate of convergence.

对几个典型的测试函数进行仿真表明,该算法较标准蜂群算法提高了全局搜索能力和收敛速度,改善了优化性能。

Many methods are used to solve nonlinear problems, their rate of convergence is quick, for example, Newton-moser method, King-werner method, they are attentioned widely because of the quick rate of convergence. While these methods are used to solve singular problems, the rate of convergence is slow, it is discommodious for us to solve practical problems.

有许多方法在求解非奇异问题时,它们的收敛率是很快的,有些甚至能达到二次收敛,例如Newton-Moser法、King-werner法,这是所熟知的,因其收敛速度快,并且简单易用而广受重(来源:AB17C论文dddd网www.abclunwen.com)视。

Firstly,based on the B.Bowermans result about the rate of convergence in Cesaro sense of certain nonhomogeneous Markov chains which the transition matrices converge,we are to study a certain nonhomogenous Markov chains which the transition matrices average converge to a period strongly ergodic stochastic matrice,and control the average convergenc rate of transition matrices,then we get the rate of convergence in Cesaro sense about the nonhomogeneous Markov chains by used the character of norm and the character of nonhomogeneous Markov chains.It is an extension of a B.

首先在B.Bowerman等人研究转移矩阵列收敛的一类非齐次马氏链,其Cesaro平均收敛的收敛速度基础上,研究转移矩阵列平均收敛到一周期强遍历随机矩阵的一类非齐次马氏链,通过控制转移矩阵列平均收敛的收敛速度,利用矩阵范数的性质、非齐次马氏链的相关性质等,得到该非齐次马氏链转移矩阵Cesaro平均收敛的收敛速度,是B。

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