广义Nekrasov矩阵的新判据

广义Nekrasov矩阵是一类应用广泛的特殊矩阵,通过构造不同的系数因子,结合不等式的放缩技巧,给出广义Nekrasov矩阵两个新的充分判据,改进和推广了近期文献的已有结果.     

一类因子试验的广义方差分析原理

本文给出了一类多因子试验的误差矩阵及效应矩阵的定义及其分布，以及这些效应矩阵与误差矩阵之间相互独立的一个充分条件；导出了计算一类特殊效应矩阵的明晰公式，从而得到了一类多因子试验“广义方差分析”的一些结果。     

解线性方程组的预条件Gauss-Seidel型迭代法

给出了解线性方程组的预条件Gauss-Seidel型方法,提出了选取合适的预条件因子．并讨论了对Z-矩阵应用这种方法的收敛性,给出了收敛最快时的系数取值．最后给出数值例子,说明选取合适的预条件因子应用Gauss-Seidel方法求解线性方程组是有效的．     

矩阵的秩的一个定理和线性方程组的同解定理

本文给出了矩阵乘积的秩定理的一个逆形式,并应用它证明了线性方程组的同解定理. 本文中的符号同[1].在[1]中有以下定理: 定理:两个矩阵的乘积的秩不大于每一因子的秩.特别,当有一个因子是可逆矩阵时,乘积的秩等于另一因子的秩.     

正交试验的广义方差分析

本文根据[1]中给出的多元线性模型中的有关结论结合实例给出了多指标正交试验结果的“广义方差分析法”,可用来对多指标试验进行因子的显著性检验,以提高—些重要项目的分析精度.     

矩阵因子分解及其应用举例

通过矩阵方程定义了矩阵的左、右因子和双因子,给出了各类因子存在的充要条件,并将其应用到满秩分解和极分解等典型例子中.论证中,采用多种观点和方法,空间映射、矩阵运算并重.     

有强法式的体上矩阵

设D为除环,A∈Dn×n,则可用初等变换将λI-A化简为对角阵A= diag(1,…,1,φ1,…,φr),其中(?)i为D上首1多项式并且φ1|…|φr.如果这个对角阵A在形状上是唯一的,则称A是有强法式的矩阵.本文应用中心原子因子与初等因子给出了体上有强法式的矩阵的本质刻画,给出了体上矩阵有强法式的一些充要条件.     

酉不变范数下极分解的扰动界

设A是m×n(m≥n)且秩为n的复矩阵.存在m×n矩阵Q满足Q*Q=I和n×n正定矩阵H使得A=QH,此分解称为A的极分解.本文给出了在任意酉不变范数下正定极因子H的扰动界,改进文[1,11]的结果;另外也首次提供了乘法扰动下酉极因子Q在任意酉不变范数下的扰动界.     

r—置换因子循环矩阵的性质

给出了r—置换因子循环矩阵的概念,并得到了一些性质,以及奇异性的判别方法。     

一种求非负不可约三对角矩阵最大特征值的方法

就非负不可约三对角矩阵,给出了一种求最大特征值的方法,关键是求迭代因子g的新方法,且证明了此迭代因子大于文献[2]中的迭代因子(r+3d)/(r+2d),从而减少了迭代次数,节约了运算时间.     

Convergence of the Multigrid Method of Ill-conditioned Block Toeplitz Systems

We study the solutions of block Toeplitz systems A _mn u = b by the multigrid method (MGM). Here the block Toeplitz matrices A _mn are generated by a nonnegative function f (x,y) with zeros. Since the matrices A _mn are ill-conditioned, the convergence factor of classical iterative methods will approach 1 as the size of the matrices becomes large. These classical methods, therefore, are not applicable for solving ill-conditioned systems. The MGM is then proposed in this paper. For a class of block Toeplitz matrices, we show that the convergence factor of the two-grid method (TGM) is uniformly bounded below 1 independent of mn and the full MGM has convergence factor depending only on the number of levels. The cost per iteration for the MGM is of O(mn log mn) operations. Numerical results are given to explain the convergence rate.     

Modulus‐based multigrid methods for linear complementarity problems

By employing modulus‐based matrix splitting iteration methods as smoothers, we establish modulus‐based multigrid methods for solving large sparse linear complementarity problems. The local Fourier analysis is used to quantitatively predict the asymptotic convergence factor of this class of multigrid methods. Numerical results indicate that the modulus‐based multigrid methods of the W‐cycle can achieve optimality in terms of both convergence factor and computing time, and their asymptotic convergence factors can be predicted perfectly by the local Fourier analysis of the corresponding modulus‐based two‐grid methods.     

正项矩阵级数的敛散性研究

本文研究了正项矩阵级数收敛的充要条件 ,从而把正项级数的收敛原理推广到了正项矩阵级数的情形 .     

Some extensions of the improved modified Gauss–Seidel iterative method for H‐matrices

In this paper, first we present a convergence theorem of the improved modified Gauss–Seidel iterative method, referred to as the IMGS method, for H‐matrices and compare the range of parameters α_i with that of the parameter ω of the SOR iterative method. Then with a more general splitting, the convergence analysis of this method for an H‐matrix and its comparison matrix is given. The spectral radii of them are also compared. Copyright © 2006 John Wiley & Sons, Ltd.     

Alternately linearized implicit iteration methods for the minimal nonnegative solutions of the nonsymmetric algebraic Riccati equations

For the non‐symmetric algebraic Riccati equations, we establish a class of alternately linearized implicit (ALI) iteration methods for computing its minimal non‐negative solutions by technical combination of alternate splitting and successive approximating of the algebraic Riccati operators. These methods include one iteration parameter, and suitable choices of this parameter may result in fast convergent iteration methods. Under suitable conditions, we prove the monotone convergence and estimate the asymptotic convergence factor of the ALI iteration matrix sequences. Numerical experiments show that the ALI iteration methods are feasible and effective, and can outperform the Newton iteration method and the fixed‐point iteration methods. Besides, we further generalize the known fixed‐point iterations, obtaining an extensive class of relaxed splitting iteration methods for solving the non‐symmetric algebraic Riccati equations. Copyright © 2006 John Wiley & Sons, Ltd.     

Convergence properties of preconditioned Hermitian and skew-Hermitian splitting methods for non-Hermitian positive semidefinite matrices

For the non-Hermitian and positive semidefinite systems of linear equations, we derive necessary and sufficient conditions for guaranteeing the unconditional convergence of the preconditioned Hermitian and skew-Hermitian splitting iteration methods. We then apply these results to block tridiagonal linear systems in order to obtain convergence conditions for the corresponding block variants of the preconditioned Hermitian and skew-Hermitian splitting iteration methods.

     

Asynchronous multisplitting iteration with different weighting schemes

The multisplitting iteration method was presented by O’Leary and White [5] for solving large sparse linear systems on parallel multiprocessor system. In this paper, we further set up an asynchronous variant for the multisplitting iteration method with different weighting schemes studied by White [8]. Moreover, we establish a general convergence criterion for asynchronous iteration framework, and then prove the convergence of the new asynchronous multisplitting iteration method with different weighting schemes by making use of this general criterion.     

Improved convergence theorems for new Hermitian and skew-Hermitian splitting methods

In this note, based on the previous work by Pour and Goughery (New Hermitian and skew-Hermitian splitting methods for non-Hermitian positive definite linear systems Numer. Algor. 69 (2015) 207–225), we further discuss this new Hermitian and skew-Hermitian splitting (described as NHSS) methods for non-Hermitian positive definite linear systems. Some new convergence conditions of the NHSS method are obtained, which are superior to the results in the above paper.     

Analyzing the convergence factor of residual inverse iteration

We will establish here a formula for the convergence factor of the method called residual inverse iteration, which is a method for nonlinear eigenvalue problems and a generalization of the well-known inverse iteration. The formula for the convergence factor is explicit and involves quantities associated with the eigenvalue to which the iteration converges, in particular the eigenvalue and eigenvector. Residual inverse iteration allows for some freedom in the choice of a vector w _k and we can use the formula for the convergence factor to analyze how it depends on the choice of w _k . We also use the formula to illustrate the convergence when the shift is close to the eigenvalue. Finally, we explain the slow convergence for double eigenvalues by showing that under generic conditions, the convergence factor is one, unless the eigenvalue is semisimple. If the eigenvalue is semisimple, it turns out that we can expect convergence similar to the simple case.     

渐近循环马氏链的收敛速度

引入了渐近循环马氏链的概念,它是循环马氏链概念的推广.首先研究了在强遍历的条件下,可列循环马氏链的收敛速度,作为主要结论给出了当满足不同条件时可列渐近循环马氏链的C-强遍历性,一致C-强遍历性和一致C-强遍历的收敛速度