该级数一致收敛于收敛环内的紧子集上。
The series converges uniformly on compact subsets of the interior of the annulus of convergence.
并对提出的算法做了一致收敛性分析。
Then uniform convergence analysis is carried out for the proposed algorithm.
最后讨论了一致收敛函数列与函数项级的性质。
Finally, out of uniform convergence of function and function of the nature of class.
本文讨论了含参量无穷积分亚一致收敛的条件。
The conditions of the sub-consistent convergence of the parameter-involved infinite integration are discussed in this paper.
另外，对于局部加密网格，该方法具有一致收敛性。
More importantly, this method also leads to uniform convergence for layer-adapted meshes.
研究广义分布参数扰动系统的变结构及其一致收敛问题。
The variable structure control problem of singular distributed parameter system is studied and uniformly convergence is considered.
讨论模糊数空间中一致收敛度量与其它常用度量之间的关系。
We investigate the relations between uniform metric and various known metrics for fuzzy Numbers very often used in the fuzzy content.
我们利用问题的渐近解证明了差分格式关于小参数的一致收敛性。
By means of the asymptotic solution of singular perturbation problem we proved the uniform convergence of this scheme with respect to the small parameter.
通过威阿斯·塔斯周围的学生，人们知道了一致收敛性的重要性。
Through Weierstrass circle of students the importance of uniform convergence was made known.
如果节点在求解区域内互异而且稠密，则近似解一致收敛到精确解。
If the grid points are different and dense in the interval of the solution, then approximate solution is convergent uniformly to the exact solution.
在分析数学中一致收敛的重要性及几乎处处收敛不一定能够一致收敛。
To make sure under what circumstances everywhere converge can be converted into uniform convergence, a typical counter-case has to be analysed.
本文研究小参数椭圆-抛物偏微分方程一致收敛差分格式的充要条件。
This paper studies the necessary and sufficient condition of uniformly convergent difference scheme for the elliptic-parabolic partial differential equation with a small parameter.
连续、一致连续、一致收敛和等度连续是函数或函数列非常重要的性质。
Continuity, uniform continuity, uniform convergence and equicontinuity are very important qualities of functions or sequence of functions.
本文给出了非一致收敛的几个定理 ，并以较多的实例说明它们的应用。
Several theorems about non-uniform convergence and a few examples were used to explain the application of them.
第二部分是在一致收敛条件下函数列、函数项级数以及含参量反常积分的性质。
The second part is in uniform convergence conditions function series, function and parameter improper integral. We properties.
本文在经典统计学习理论的基础上，讨论了可能性空间上学习过程一致收敛速度的界。
In this paper, the bounds on the rate of uniform convergence of the learning processes on possibility space are discussed based on the classic Statistical learning Theory.
最后证明基于双重随机样本的统计学习理论的关键定理并讨论学习过程一致收敛速度的界。
Finally the key theorem of statistical learning theory based on random rough samples is proved, and the bounds on the rate of uniform convergence of learning process are discussed.
在论证过程中充分利用了解析函数的性质，系统推导了内闭一致有界与内闭一致收敛的关系。
The author also studies the relationship between internally closed uniform bound and internally closed uniform convergence.
和人们对模糊数空间的常识相反，本文中证明了的确一致收敛度量与其它度量之间有内在的联系。
We find that, contrary to ordinary conception, there are indeed some internal relations between the uniform metric and metrics commonly used.
试验证明，当采用所提出的“混合比例分割法”时，能同时获得快的收敛速度和良好的一致收敛性。
Experimental results show that the merits in the respects of interactive speed and consistent convergence can be gained, when the mixed proportional division method proposed here is applied.
基于状态空间分析，给出了连续随机信号建模的时间序列分析方法，并证明了参数估计的一致收敛性。
Based on the state space analysis, the time series analysis method for identification of the stochastic continuous signals, proved as consistent convergence, is given.
理论分析和仿真结果都表明估计结果具有渐近无偏性和一致收敛性，该方法辨识精度高，具有良好的实用性。
The theory analysis and simulation results show that the estimation is asymptotically unbiased and has strong consistency, and that the new method is very efficient and practical.
本文在截尾样本下构造了失效率的一种截尾非参数估计，并给出了其均方收敛及强相合性的局部一致收敛速度。
In this paper, a nonparametric estimator terminated of failure rate is constructed based on censored data, and its rates of convergence in mean square and strong consistency are given respectively.
其次，构造了该问题族的由精确线性项和非线性补偿项组成的解序列，并证明了解序列一致收敛到系统的最优解。
Then a solution sequence, which consists of an accurate linear term and nonlinear compensation term, is constructed and its uniform convergence to the optimal solution of the system is proven.
本文在原有研究结果的基础上，讨论了叙列空间上的弱k级有界变差函数的一致收敛问题，得到了若干有关一致收敛的等价条件。
In this paper, based on -, the uniform convergence of the Kth order weak bounded variation functions on the sequence Spaces were investigated. Some equivalent conditions were also obtained.
对于函数级数，研究其和函数的解析性质很重要，但函数级数必须具有一致收敛性，而判断函数级数的一致收敛性往往是比较困难的。
However, this study should be based on the fact that the series must have consistent convergence, the judgment of which is rather difficult.
但是，从一致性方面来看，只提供收敛一致性。
However, from a consistency perspective, only convergent consistency is given.
支持向量机(SVM)是一种新的通用学习机器，它从结构风险最小化的角度，分析了学习过程的一致性、收敛速度等。
Support vector machine (SVM) is a new general learning machine, which analyzes the consistency of learning and speed of convergence from structure risk minimization principle.
在这篇文章中，我们提出了最近邻估计在任意紧集上一致强收敛速度的概念，得到了一些较好的收敛速度。
In this paper, we propose the concept of rates of strong uniform convergence of nearest neighbor density estimates on any compact set and obtain some better convergence rates.
计算机仿真结果与理论分析相一致，证实了该算法比通常的补对算法和传统的LMS算法有更快的收敛速度。
Computer simulation results confirms the theoretical analysis and shows the new algorithm provides faster convergence speed than the complementary pair algorithm and usual LMS algorithm.
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