H-矩阵线性方程组的一类预条件并行多分裂SOR迭代法

基于并行多分裂算法的思想及SOR迭代格式, 本文提出一种求解H-矩阵线性方程组新的并行多分裂SOR迭代法, 新方法某种程度上避免了SOR迭代法中选取最优参数的困难. 同时, 选取Kohno等(1997)提出的预条件子$P=I+S_{\alpha}$对原始线性方程组进行预处理, 进而给出了一种实用的预条件并行多分裂SOR迭代法. 理论分析和数值实验均表明, 新算法是实用而有效的.     

解线性方程组迭代法的若干几何研究

从解线性方程组迭代法入手,提出了两个迭代法的基本几何过程,揭示了著名的Jacobi迭代法、Gauss-Seidel迭代法和SOR方法等迭代法的几何实质、重新认识了这些经典的迭代过程,同时揭示了解线性方程组的克兰姆法则与迭代法的关系.同时从几何出发设计了一种解线性方程组的迭代方法.     

水平线性互补问题投影迭代法和模系矩阵分裂迭代法的等价性

水平线性互补问题(HLCP)是著名线性互补问题(LCP)的重要推广形式之一,投影迭代法和模系矩阵分裂迭代法是最近提出的求解HLCP两类非常有效的热点方法.本文研究表明,尽管这两类方法导出原理不同,但在一定条件下是等价的.特别地,当模系矩阵分裂迭代法中参数矩阵Ω取为特定的正对角矩阵时,投影Jacobi法、投影Gauss-Seidel法和投影SOR法分别等价于模系Jacobi迭代法、加速的模系Gauss-Seidel迭代法和加速的模系SOR迭代法.此外,对一般的正对角矩阵Ω,本文也研究了两类方法的等价性.最后,通过数值算例验证了本文的理论结果.     

SOR方法的拓展与应用

对流体润滑的压力控制方程,在有限差分法的基础上,通过对SOR超松弛因子和迭代精度的选择,采用SOR逐次超松弛迭代法对控制方程进行了数值求解.在保证方程求解精度的基础上,还具有收敛快、稳定性好,计算工作量小等特点.     

凝固过程的温度场数值模拟

通过对铸件凝固过程中各换热边界条件的研究,建立了凝固过程的二维非稳态温度场计算数学模型;并运用了有限差分方法对模型进行离散,得到大型方程组,并利用超松驰迭代法(即SOR法)解该方程组,据此,利用Turbo C编制了计算机程序.上机运行结果表明,可较满意地模拟凝固过程温度场的分布.     

AOR迭代法的收敛性

1.引言 [1]定义了解线性方程组A_x=b的AOR迭代法,它以SOR迭代为特例,而且适当选取参数,有可能比SOR方法收敛快(见[2]).众所周知,使 AOR方法有意义的最基本条件是A的对角元素都不为零.然而,在实际计算中,有时需要求解的线性方程组其系数矩阵存在零对角元素.例如[3]中研究的线性方程组的系数矩阵具有如下形式:     

IMGS方法对于,H -矩阵的若干令人满意的改进

该文给出线性方程组改进的Gauss-Seidel迭代法（被称之为IMGS方法）对于H -矩阵的收敛性定理,并且对其参数a_i与SOR迭代法的参数ω的取值范围进行了比较. 所用方法及所得结论优于近年来相关结论,并且表明这种IMGS方法对,H -矩阵是有效的.     

ATOR迭代法的收敛性

本文定义了广义ATOR迭代法,并给出了该方法的Stein-Rosenberg型定理和Ostrows-ki-Reich型定理,广义ATOR方法的单调收敛界及其与SOR法的比较也在本文给予讨论。     

SOR迭代法的误差分析

§1 引言解线性方程组Ax=b的SOR迭代法按如下公式进行计算:     

非线性υ-循环系统的SOR迭代法

0引言 1971年Rheinboldt~[16]根据Ortega的一篇未发表的短文，将M-矩阵的概念推广到非线性函数。其后，由More,Rheinboldt进步将Fiedler和Ptek~[4]定义过的P-矩阵，S-矩阵等矩阵类推广到非线性函数。同时，他们还研究了M-函数的非线性Gauss-Seidel迭代法和非线性SOR迭代法的收敛性问题~([11][17])。1986年，Alefeld和Volkmann研究了M-函数的SSOR迭代法~[1]。1991年Frommer将广义对角矩阵推广到非线性函数，并讨论了M-函数的异步非线性JOR，SOR和SSOR迭代法的收敛性~[6]。     

Block SOR methods for rank-deficient least-squares problems

Many papers have discussed preconditioned block iterative methods for solving full rank least-squares problems. However very few papers studied iterative methods for solving rank-deficient least-squares problems. Miller and Neumann (1987) proposed the 4-block SOR method for solving the rank-deficient problem. Here a 2-block SOR method and a 3-block SOR method are proposed to solve such problem. The convergence of the block SOR methods is studied. The optimal parameters are determined. Comparison between the 2-block SOR method and the 3-block SOR method is given also.     

Preconditioned sor methods for generalized least-squares problems

1.IntroductionThegeneralizedleastsquaresproblem,definedasmin(Ax--b)"W--'(Ax--b),(1.1)xacwhereAERm",m>n,bERm,andWERm'misasymmetricandpositivedefinitematrix,isfrequentlyfoundwhensolvingproblemsinstatistics,engineeringandeconomics.Forexample,wegetgeneralizedleastsquaresproblemswhensolvingnonlinearregressionanalysisbyquasi-likelihoodestimation,imagereconstructionproblemsandeconomicmodelsobtainedbythemaximumlikelihoodmethod(of.[1,21).Paige[3,4]investigatestheproblemexplicitly.Hechangestheorig…     

矩阵分裂序列与线性二级迭代法

本文讨论线性非定常二级迭代法的收敛性．对于一般的基于矩阵分裂序列的迭代法,针对分裂序列本身找到了一种新的且相对较弱的收敛性条件,并因此得到了由非定常二级迭代法推广而来的广义二级迭代法的收敛结果．从而,用一种新的方法证明了非定常二级迭代法的收敛性．     

A note on Hermitian splitting induced relaxation methods for convection-diffusion equations

The solution of the linear system Ax = b by iterative methods requires a splitting of the coefficient matrix in the form A = M − N where M is usually chosen to be a diagonal or a triangular matrix. In this article we study relaxation methods induced by the Hermitian and skew-Hermitian splittings for the solution of the linear system arising from a compact fourth order approximation to the one dimensional convection-diffusion equation and compare the convergence rates of these relaxation methods to that of the widely used successive overrelaxation (SOR) method. Optimal convergence parameters are derived for each method and numerical experiments are given to supplement the theoretical estimates. For certain values of the diffusion parameter, a relaxation method based on the Hermitian splitting converges faster than SOR. For two-dimensional problems a block form of the iterative algorithm is presented. © 1998 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 14: 581–591, 1998     

Generalized iterative methods for semidefinite linear systems

We consider iterative methods for semidefinite systems Ax = b based on splittings A = B ? C, where B is not necessarily nonsingular. Necessary and sufficient conditions for convergence are obtained. These are then used to obtain convergence results for block SOR, block SSOR, and block JOR methods for matrices with semidefinite block diagonal.     

Splitting iterative methods for fuzzy system of linear equations

A class of splitting iterative methods is considered for solving fuzzy system of linear equations, which cover Jacobi, Gauss–Seidel, SOR, SSOR, and their block variants proposed by others before. We give a convergence theorem for a regular splitting, where the corresponding iterative methods converge to the strong fuzzy solution for any initial vector and fuzzy right-hand vector. Two schemes of splitting are given to illustrate the theorem. Numerical experiments further show the efficiency of the splitting iterative methods.     

On the supports of functions

In this paper, finite difference and finite element methods are used with nonlinear SOR to solve the problems of minimizing strict convex functionals. The functionals are discretized by both methods and some numerical quadrature formula. The convergence of such discretization is guaranteed and will be discussed. As for the convergence of the iterative process, it is necessary to vary the relaxation parameter in each iterations. In addition, for the model catenoid problem, boundary grid refinements play an essential role in the proposed nonlinear SOR algorithm. Numerical results which illustrate the importance of the grid refinements will be presented.

     

Semiconvergence of extrapolated iterative methods for singular linear systems

In this paper, we discuss convergence of the extrapolated iterative methods for solving singular linear systems. A general principle of extrapolation is presented. The semiconvergence of an extrapolated method induced by a regular splitting and a nonnegative splitting is proved whenever the coefficient matrix A is a singular M-matrix with ‘property c’ and an irreducible singular M-matrix, respectively. Since the (generalized, block) JOR and AOR methods are respectively the extrapolated methods of the (generalized, block) Jacobi and SOR methods, so the semiconvergence of the (generalized, block) JOR and AOR methods for solving general singular systems are proved. Furthermore, the semiconvergence of the extrapolated power method, the (block) JOR, AOR and SOR methods for solving Markov chains are discussed.     

Block SOR methods for fuzzy linear systems

In this paper, the block SOR iterative methods are studied for n×n fuzzy linear systems and the corresponding convergence theorems are also given out. We know that the coefficient matrix S of the augmented system SX=Y is consistently ordered when S ₁ is nonsingular, and in this case the optimal parameter ω of the block SOR method is obtained. Numerical examples are presented to illustrate the theory.     

Asynchronous two-stage iterative methods

Summary. Parallel block two-stage iterative methods for the solution of linear systems of algebraic equations are studied. Convergence is shown for monotone matrices and for -matrices. Two different asynchronous versions of these methods are considered and their convergence investigated. Received September 7, 1993 / Revised version received April 21, 1994