广义严格对角占优矩阵新的判定准则

In this paper we provide the new criteria for a strictly generalized diagonally dominant matrix, and it proves by an example that the results of this paper extend the results in[6]. In addition, we obtain the criteria of the nonsingular M-matrix.     

求解加权线性最小二乘问题的预处理迭代方法

给出了求解一类加权线性最小二乘问题的预处理迭代方法,也就是预处理的广义加速超松弛方法（GAOR）,得到了一些收敛和比较结果．比较结果表明当原来的迭代方法收敛时,预处理迭代方法会比原来的方法具有更好的收敛率．而且,通过数值算例也验证了新预处理迭代方法的有效性．     

基于梯度的Sylvester共轭矩阵方程的迭代解

本文提出了一种基于梯度的Sylvester共轭矩阵方程的迭代算法.通过引入一个松弛参数和采用递阶辨识原理,构造一个迭代算法求解Sylvester矩阵方程.通过应用复矩阵的实数表达以及实数表示的一些性质,收敛性分析表明在一定假设条件下,对于任意初始值,迭代方法均收敛到精确解,数值算例也表明了所给方法的有效性.     

阶梯矩阵及其一般化在迭代法中的应用

Lu Hao首先给出了阶梯矩阵及其一般性的定义和性质．这类矩阵为迭代法提供了新矩阵分裂的基础．基于此新矩阵类的迭代方法的显著特征是它对于并行计算很容易被实现．应用这一新的分解方法,给出了一般的加速松弛方法（GAOR）,而关于AOR方法的一些性质可以被延伸到该新方法中,并针对Hermite正定矩阵进行了新方法收敛性的分析．最后,给出了一些例子来表明新方法的优越性．     

求解M-张量方程的两种新型算法

多重线性系统在当今的工程计算和数据挖掘等领域有很多实际应用,许多问题可以转化为多重线性系统求解问题.在本文中,我们首先提出了一种新的迭代算法来求解系数张量为M-张量的多重线性系统,在此基础上又提出了一种新的改进算法,并对两种算法的收敛性进行了分析.数值算例的结果表明,本文提出的两种算法是有效的并且改进算法的迭代时间更少.     

APPLICATIONS OF STAIR MATRICES AND THEIR GENERALIZATIONS TO ITERATIVE METHODS

Stair matrices and their generalizations are introduced. The definitions and some properties of the matrices were first given by Lu Hao. This class of matrices provide bases of matrix splittings for iterative methods. The remarkable feature of iterative methods based on the new class of matrices is that the methods are easily implemented for parallel computation. In particular, a generalization of the accelerated overrelaxation method (GAOR) is introduced. Some theories of the AOR method are extended to the generalized method to include a wide class of matrices. The convergence of the new method is derived for Hermitian positive definite matrices. Finally, some examples are given in order to show the superiority of the new method.     

Preconditioned iterative methods for solving weighted linear least squares problems

A class of preconditioned iterative methods,i.e.,preconditioned generalized accelerated overrelaxation(GAOR) methods,is proposed to solve linear systems based on a class of weighted linear least squares problems.The convergence and comparison results are obtained.The comparison results show that the convergence rate of the preconditioned iterative methods is better than that of the original methods.Furthermore,the effectiveness of the proposed methods is shown in the numerical experiment.     

求解Time-dependent Stokes方程的含参数双预优迭代算法

Time-dependent Stokes方程在离散动力学系统和科学计算中具有非常重要的作用,而它的求解非常困难.针对Time-dependent Stokes方程利用双预优方法构造了一种新型的含参数双预优迭代解法,并给出了新方法的收敛性分析,同时还讨论了参数的取值范围.最后用数值算例又验证了新方法的可行性和有效性.     

Modified iterative method for augmented system

The successive overrelaxation-like(SOR-like) method with the real parameters ω is considered for solving the augmented system. The new method is called the modified SOR-like(MSOR-like) method. The functional equation between the parameters and the eigenvalues of the iteration matrix of the MSOR-like method is given. Therefore, the necessary and sufficient condition for the convergence of the MSOR-like method is derived. The optimal iteration parameter ω of the MSOR-like method is derived. Finally, the proof of theorem and numerical computation based on a particular linear system are given, which clearly show that the MSOR-like method outperforms the SOR-like(Li, C. J., Li, B. J., and Evans, D. J. Optimum accelerated parameter for the GSOR method. Neural, Parallel Scientific Computations, 7(4), 453–462(1999)) and the modified symmetric SOR-like(MSSOR-like) methods(Wu, S. L., Huang, T. Z., and Zhao, X. L. A modified SSOR iterative method for augmented systems.     

数值分析课程教学改革的探索与实践

分析了当前数值分析课程教学存在的一些问题,结合多年的本科生和研究生的教学实践,给出了数值分析课程教学改革的具体措施,总结了改革的效果.