非中心差商收敛性与可导性

引入非中心差商极限概念 ,讨论了非中心差商极限存在与可导的关系 。

半正定线性系统广义非定常多分裂二阶段迭代方法的收敛性

为了高效求解正定或半正定的大型稀疏线性方程组,在第一阶段采用经典矩阵分裂的基础上,广义非定常多分裂二阶段迭代方法的第二阶段分裂融合了多分裂和矩阵预处理技术,对非定常多分裂二阶段迭代方法进行了推广。为了研究收敛性,将该迭代方法的算法形式和逻辑语言表达形式改写为紧凑的迭代格式。由此得到,广义非定常多分裂二阶段迭代算法在一个充分条件下收敛。最后,具有五对角系数矩阵的大型稀疏线性系统的数值算例验证了广义非定常多分裂二阶段迭代算法的普适性,并且从迭代次数和CPU时间上体现了算法的高效性。

指数为1的半正定线性系统迭代方法的收敛性

当相容奇异线性系统系数矩阵的指数为1时,文章利用群逆的概念来介绍广义固定迭代方法半范数收敛,商收敛和收敛三者之间的关系,然后再利用群逆的概念来研究广义固定迭代方法半范数收敛的新条件.在保证迭代格式收敛的前提下,该条件比Keller的P-正则条件要弱.

半正定系统广义非定常多分裂迭代算法

文章首先给出了广义非定常多分裂算法,并且证明了在一个简洁条件下广义多分裂算法一定半范数收敛,进一步可得到该算法商收敛,该结果是对Cao[2]中结论的推广。

The Equivalence Theorem of Appoximation for Two-dimensional Baskakov Operators

In this paper, we study the convergence rate of two-dimensional Baakakov operators with Jacobi-weights and the approximation equivalence theorem is obtained, making use of multivariate decompose skills and results of one-dimensional Baskakov operators.

A General Projection Method for a System of Relaxed Coercive Variational Inequalities in Hilbert Spaces

In this paper,we consider a new algorithm for a generalized system for relaxed coercive nonlinear inequalities involving three different operators in Hilbert spaces by the convergence of projection methods.Our results include the previous results as special cases extend and improve the main results obtained by many others.

(L,M)-fuzzy收敛空间范畴中的始结构与终结构

定义了LX上的M-滤子,研究了LX上的M-滤子的交、并、乘积等运算,证明了(L,M)-fuzzy收敛空间范畴是一个拓扑范畴并给出了始结构与终结构的构造,在此基础上给出了乘积(L,M)-fuzzy收敛空间、余积(L,M)-fuzzy收敛空间以及商(L,M)-fuzzy收敛空间的概念。

On convergence of the inexact Rayleigh quotient iteration with the Lanczos method used for solving linear systems

For the Hermitian inexact Rayleigh quotient iteration （RQI）, we consider the local convergence of the inexact RQI with the Lanczos method for the linear systems involved. Some attractive properties are derived for the residual, whose norm is ξk, of the linear system obtained by the Lanczos method at outer iteration k ＋ 1. Based on them, we make a refined analysis and establish new local convergence results. It is proved that （i） the inexact RQI with Lanezos converges quadratically provided that ξk ≤ξ with a constant ξ≥） 1 and （ii） the method converges linearly provided that ξk is bounded by some multiple of 1/‖τk‖ with ‖τk‖ the residual norm of the approximate eigenpair at outer iteration k. The results are fundamentally different from the existing ones that always require ξk 〈 1, and they have implications on effective implementations of the method. Based on the new theory, we can design practical criteria to control ξk to achieve quadratic convergence and implement the method more effectively than ever before. Numerical experiments confirm our theory and demonstrate that the inexact RQI with Lanczos is competitive to the inexact RQI with MINRES.