- 更多网络例句与非收敛的相关的网络例句 [注：此内容来源于网络，仅供参考]
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Based on the measurement and calculation of Chinese agricultural Total Factor Productivity using the non-parameter Data Envelopment Analysis and Malmquist productivity index approach,the paper has tested the convergence hypothesis of the agricultural TFP growth in China for the transformational period(1978~2005),and this includes the σ convergence,unconditional β convergence and the conditional β convergence.
在利用非参数的DEA曼奎斯特生产率指数方法对中国农业全要素生产率进行求解的基础上，论文运用经济增长收敛理论对农业TFP(Total Factor Produc-tivity)增长在1978~2005年转型期的收敛性情况进行检验，这包括从σ收敛、绝对β收敛到条件β收敛的全面检验。
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A stable convergence calculation method using Newton homotopy continuation method based on the non-equilibrium rate model was established.
建立了非平衡级速率模型，采用收敛性能很好的Newton同伦连续算法，在计算中合理地引入阻尼因子，建立了可稳定收敛的计算方法。
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In the case of NA samples, the parameter for scale exponential family is discussed using empi- rical Bayes methods. Moreover, we investigate the statistical analysis of life data in reliability tests. Firstly, based on the LINEX loss function, we obtain the empirical Bayesian estimator for parameter of the one-side truncated-type distribution families and the scale exponential family under NA samples, also discuss the estimators?
在非对称的LINEX损失函数下，我们首先给出了一类单边截断型分布族、刻度指数族参数的经验Bayes估计NA样本情形），并讨论了该估计的收敛性质，在某些条件下，证明了本文给出的经验Bayes估计是渐近最优的，且给出了收敛速度。
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On the basis of least potential energy theory the stability and convergence are analyzed and discussed in Hilbert space, and the basic condition ensuring uniqueness and convergence of solution is given.
在Hilbert空间内，从最小势能原理出发对非协调数值流形方法的稳定性和收敛性进行了分析和讨论，得到了保证非协调流形元解唯一存在和收敛的基本条件，完善了非协调数值流形方法的理论基础。
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Based on contraction mapping theorem of analysis mathematics, the non-steady flow mathematical model of mine ventilation network was analyzed.
利用分析数学的压缩映射原理，对矿井通风网络非稳定流动数学模型进行了分析，得出了数学模型数值解收敛的条件，确定了以惯性系数排序选择最小生成树的回路选择方案，为矿井通风网络非稳定流动数学模型数值解的收敛性提供了理论依据。
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To examine the topological space theory by nonstandard analysis, the nonstandard characteristics of ideals convergence is given in the enlargement model.
为了用非标准分析方法进一步研究拓扑空间，在扩大模型下，对理想收敛的基本理论进行了非标准刻画：设X是拓扑空间，I是X中的理想，I收敛于点x，当且仅当v v 。
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This paper discusses convergence of Ishikawa iteration sequence and existence of fixed points for set-valued nonexpansive mapping in uniformly covex Banach space, and the conditions are shown which guarantee the convergence of the iteration sequence to a fixed point.
讨论了δ集值非扩张映象在一致凸Banach空间中不动点非空的充分必要条件与Ishikawa迭代序列的收敛性及确保迭代程序收敛到不动点的条件，所得结果是单值非扩张映象的推广和发展。
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To solve it, we turn it into nonsmooth equations, utilizing inexact theory we give an inexact generalized Newtons method and under some mild conditions we prove that it is global convergence and superlinear convergence .
首先将其约束问题的求解转化为非光滑方程组的求解，然后利用不完全求解理论给出了一个非精确的广义牛顿算法，在一定的条件下证明了算法的全局收敛性和局部超线性收敛性并给出了LC~1非线性约束问题的收敛性条件。
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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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We show that the hybrid method is globally and superlinearly convergent for nonzero residual problems and globally and quadratically for zero residual problems.
因此，该杂交方法对于零残量问题是二阶收敛的，而对于非零残量问题是超线性收敛的。
- 更多网络解释与非收敛的相关的网络解释 [注：此内容来源于网络，仅供参考]
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Divergence：发散
数学分析中的收敛:1.收敛数列令为一个数列,且A为一个固定的实数,如果对于任意给出的b>0,存在一个正整数N,使得对于任意n>N,有|an-A|<b,则数列存在极限A,数列被称为收敛. 非收敛的数列被称作"发散"(divergence)数列.
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Oscillatory：振荡
线性模型的时间路径无非四种:振荡(oscillatory)收敛;振荡发散;非振荡收敛;非振荡发散. 对于路径上的一些突然的变化就要依赖于随机冲击的扰动. 混沌(非线性)模型的本质是确定性的(deterministic),区别于stochastic linear model,用非线性方程来刻画路径上的qualitative changes.
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output function：输出函数
2-x迭代误差小于指定值;3-fval迭代误差小于指定值;4-搜索方向的幅值小于指定值;0-迭代次数超过最指定数(Maxlter)或者fval超过指定值(Funs);-1-算法终止按照输出函数(output function);-2-貌似算法收敛于非零跟;