非线性sine-Gordon方程的双线性元分析及外推

研究双线性元对一类非线性sine-Gordon方程的有限元逼近.利用该元的高精度结果和对时间t的导数转移技巧,得到了H~1模意义下的超逼近性.进一步地,通过运用插值后处理技术,给出了H~1模意义下的超收敛结果.与此同时,通过构造一个新的外推格式,导出了与线性问题情形相同的三阶外推解.最后给出了一种全离散逼近格式下的最优误差估计.     

板问题多重网格法收敛性的低模估计

１．引言 近年来,多重网格法已成为行之有效的偏微分方程数值解法．对板问题有限元离散系统的多重网格法,也有不少的研究工作,如［４］,［５］,［１０］,［１３－１７］．在［４］,［１４－１７］中,作者讨论了Ｃ１协调元离散板问题的多重网格法,并在能量模（即 Ｈ２模）意义下获得了最优的收敛率．在［５］,［１０］中,作者讨论了非协调元离散问题的多重网格法,并在能量模意义下获得了最优的收敛率,同时在能量模意义下证明了套迭代多重网格法一阶收敛．但对板问题多重网格法的低模估计,即 Ｈ１模估计,至今尚未见研究,本文…     

加罚N-S方程的有限元非线性Galerkin方法

非线性Galerkin方法是对耗散型非线性发展方程的一种数值解法,其空间变量不象一般Galerkin方法那样在线性空间上离散,而是在非线性流形上离散,所得逼近解在时间变量增大时可以更快地逼近其精确解.精细的理论分析可见[1],[2]等,在有限元逼近基础上将此方法应用到Navier-Stokes方程上的工作可参见[3],[4],这些文章主要针对速度与压力同时求解的混合元情形做了讨论.本文在[4]的基础上对加罚Navier-Stokes方程的一种非线性Galerkin方法的半离散和全离散有限元逼近格式分别进行了误差估     

加罚N-S方程的有限元非线性Galerkin方法

非线性Galerkin方法是对耗散型非线性发展方程的一种数值解法,其空间变量不象一般Galerkin方法那样在线性空间上离散,而是在非线性流形上离散,所得逼近解在时间变量增大时可以更快地逼近其精确解.精细的理论分析可见[1],[2]等,在有限元逼近基础上将此方法应用到Navier-Stokes方程上的工作可参见[3],[4],这些文章主要针对速度与压力同时求解的混合元情形做了讨论.本文在[4]的基础上对加罚Navier-Stokes方程的一种非线性Galerkin方法的半离散和全离散有限元逼近格式分别进行了误差估     

二次Lagrangian有限元方程的几何多重网格法

为了构造快速求解二次Lagrangian有限元方程的几何多重网格法,在选择二次Lagrangian有限元空间和一系列线性Lagrangian有限元空间分别作为最细网格层和其余粗网格层以及构造一种新限制算子的基础上,提出了一种新的几何多重网格法,并对它的计算量进行了估计.数值实验结果,与通常的几何多重网格法和AMG01法相比,表明了新算法计算量少且稳健性强.     

Sobolev方程的一类各向异性非协调有限元逼近

在各向异性网格下,分别讨论了Sobolev方程在半离散和全离散格式下的一类非协调有限元逼近,得到了与传统有限元方法相同的误差估计和一些超逼近性质.同时在半离散格式下,通过构造具有各向异性特征的插值后处理算子得到了整体超收敛结果.     

双曲型方程的一类各向异性非协调有限元逼近

在各向异性条件下,讨论了双曲型方程的一类非协调有限元逼近,给出了半离散格式下的最优误差估计.同时通过新的技巧和精细估计得到了一些超逼近性质和超收敛结果.     

双曲积分微分方程的各向异性非协调有限元逼近

讨论了双曲积分微分方程在半离散格式下的一类各向异性非协调有限元逼近,得到了与传统有限元方法相同的最优误差估计和超逼近性质.同时利用插值后处理技术得到了整体超收敛结果.     

半线性椭圆型问题Mortar有限元逼近的瀑布型多重网格法

Mortar有限元法作为一个非协调的区域分解技术已得到许多研究者的关注(如文献[2]、[5]等)。本文对半线性椭圆型问题的Mortar有限元逼近提出了瀑布型多重网格法,并给出了此法的误差估计和计算复杂度估计定理。     

拟线性Sobolev方程Carey元解的高精度分析

在一种半离散格式下讨论了拟线性Sobolev方程Carey元的超收敛及外推.根据Carey元的构造证明了其有限元解的线性插值与三角形线性元的解相同,再结合线性元的高精度分析和插值后处理技巧导出了超逼近和整体超收敛及后验误差估计.与此同时,根据线性元的误差渐近展开式,构造了一个新的辅助问题,得到了比传统的有限元误差高三阶的外推结果.     

广义函数Denjoy积分的收敛性问题

本文讨论广义函数De njoy积分的收敛性问题.首先给出了广义Denjoy可积函数空间中强收敛、弱收敛、弱~*收敛和广义函数Denjoy积分收敛的关系;证明拟一致收敛是广义函数Denjoy积分收敛的一个充分必要条件;最后指出了Denjoy可积广义函数列弱~*收敛与强收敛等价当且仅当原函数等度连续.     

On the convergence of uncertain sequences

Uncertain variables are measurable functions from uncertainty spaces to the set of real numbers. In this paper, a new kind of convergence, convergence uniformly almost surely (convergence uniformly a.s.), is presented. Then, relations between convergence uniformly almost surely and convergence almost surely (convergence a.s.), convergence in measure, convergence in mean, and convergence in distribution are discussed.     

The convergence space of minimal USCO mappings

A convergence structure generalizing the order convergence structure on the set of Hausdorff continuous interval functions is defined on the set of minimal usco maps. The properties of the obtained convergence space are investigated and essential links with the pointwise convergence and the order convergence are revealed. The convergence structure can be extended to a uniform convergence structure so that the convergence space is complete. The important issue of the denseness of the subset of all continuous functions is also addressed.      

Rates of Ideal Convergence for Approximation Operators

In this paper, we study a general Korovkin-type approximation theory by using the notion of ideal convergence which includes many convergence methods, such as, the usual convergence, statistical convergence, A-statistical convergence, etc. We mainly compute the rate of ideal convergence of sequences of positive linear operators.     

Lacunary equi-statistical convergence of positive linear operators

In this paper, the concept of lacunary equi-statistical convergence is introduced and it is shown that lacunary equi-statistical convergence lies between lacunary statistical pointwise and lacunary statistical uniform convergence. Inclusion relations between equi-statistical and lacunary equi-statistical convergence are investigated and it is proved that, under some conditions, lacunary equi-statistical convergence and equi-statistical convergence are equivalent to each other. A Korovkin type approximation theorem via lacunary equi-statistical convergence is proved. Moreover it is shown that our Korovkin type approximation theorem is a non-trivial extension of some well-known Korovkin type approximation theorems. Finally the rates of lacunary equi-statistical convergence by the help of modulus of continuity of positive linear operators are studied.      

On conditional weak convergence

In this paper we discuss a number of technical issues associated with conditional weak convergence. The main modes of convergence of conditional probability distributions areuniform, probability, andalmost sure convergence in the conditioning variable. General results regarding conditional convergence are obtained, including details of sufficient conditions for each mode of convergence, and characterization theorems for uniform conditional convergence.     

Convergence of sequences of semi-continuous functions

In this paper we investigate how three well-known modes of convergence for (real-valued) functions are related to one another. In particular, we consider order convergence, pointwise convergence and continuous convergence of sequences of nearly finite normal lower semi-continuous functions. There is a natural comparison to be made between the results we obtain for convergence of sequences of semi-continuous functions, and classic results on the convergence of sequences of measurable functions.     

Convergence on Categories

We introduce and study a concept of a convergence structure on a concrete category. The concept is based on using certain generalized filters for expressing the convergence. Some basic properties of the convergence structures are discussed. In particular, we study convergence separation and convergence compactness and investigate relationships between the convergence structures and the usual closure operators on categories. Dedicated to Professor E. Giuli and Professor G. Preuss on the occasion of their 65th birthdays.     

Inequalities and Convergence Concepts of Fuzzy and Rough Variables

It is well-known that Markov inequality, Chebyshev inequality, Hölder's inequality, and Minkowski inequality are important and useful results in probability theory. This paper presents the analogous inequalities in fuzzy set theory and rough set theory. In addition, sequence convergence plays an extremely important role in the fundamental theory of mathematics. This paper presents four types of convergence concept of fuzzy/rough sequence: convergence almost surely, convergence in credibility/trust, convergence in mean, and convergence in distribution. Some mathematical properties of those new convergence concepts are also given.     

On convergence of extremes under power normalization

In this note, we discuss two aspects of convergence of extremes under power normalization: convergence of moments and convergence of densities. The moments convergence is established for four p-max-stable laws according to conditions imposed on the considered distributions or on the parameter of the p-max-stable laws. For densities convergence, local uniform convergence of the densities is shown to coincide with some von Mises conditions.