m个对角元有正增量的对称正定方程组的解

1　引　　言某些问题的数值求解要作迭代计算 ,每次迭代需求解一个系数矩阵仅有少量变化的线性方程组 .如何减少求解该方程组的计算量 ,便成为提高总体计算效率的关键之一 .这类问题往往在一些优化问题的求解过程中遇到[1] ,因此值得研究 .为此考虑如下的问题Ⅰ .问题Ⅰ　设某问题的数值求解过程要作迭代计算 ,每次迭代需求解一个线性方程组(Ａ+Ｄ)Ｘ =ｂ ( 1 .1 )其中Ａ为ｎ阶对称正定矩阵 ,ｂ为已知向量 ,Ｄ =ｄｉａｇ(ｄ1,ｄ2 ,… ,ｄｎ) ,( 1 .2 )且Ｄ的对角元ｄｉｋ>0 ,ｋ =1 ,2 ,… ,ｍ ,1≤ｉ1<ｉ2 <… <ｉｍ ≤ｎ ,ｄｉｋ及其位置和…     

两个Toeplitz矩阵相乘的一种快速算法

通过将两个Toeplitz矩阵拼凑成两个高阶上下三角形Toeplitz矩阵,构造出一种两个Toeplitz矩阵相乘的快速算法,其乘法运算次数为3n2-3n+1.     

广义鞍点问题的块三角预条件子

本文对Golub和Yuan(2002)中给出的ST分解推广到广义鞍点问题上,给出了三种块预条件子,并重点分析了其中两种预条件子应用到广义鞍点问题上所得到的对称正定阵,得出了其一般的性质并重点研究了预处理矩阵条件数的上界,最后给出了数值算例.     

对称正定Toeplitz方程组的多级迭代求解

二级迭代法亦称内外迭代法. 多级迭代法由多个二级迭代嵌套而成.这些方法特别适合于并行计算,同时可以理解为古典迭代法的延伸或共轭梯度法的预处理子.本文讨论了对称正定Toeplitz线性方程组多级迭代法. 首先,基于Toeplitz矩阵的结构, 我们给出了多级块Jacobi分裂,然后证明了每一级分裂均为P-正则分裂, 并证明了当每一级内迭代次数均为偶数时,迭代法的收敛性. 最后通过数值实例验证了此方法的有效性.     

Toeplitz方程组极小范数最小二乘解的快速算法

给出了求以m×n阶Toeplitz矩阵为系数阵的线性方程组极小范数最小二乘解的快速算法.     

解线性互补问题的预处理加速模Gauss-Seidel迭代方法

本文提出了解线性互补问题的预处理加速模系Gauss-Seidel迭代方法,当线性互补问题的系统矩阵是M-矩阵时证明了方法的收敛性,并给出了该预处理方法关于原方法的一个比较定理.数值实验显示该预处理迭代方法明显加速了原方法的收敛.     

Toeplitz型矩阵的逆矩阵的快速三角分解算法

针对有关“型”矩阵的三角分解问题 ,提出了一种 Toeplitz型矩阵的逆矩阵的快速三角分解算法 .首先假设给定 n阶非奇异矩阵 A,利用一组线性方程组的解 ,得到 A- 1的一个递推关系式 ,进而利用该关系式得到 A- 1的一种三角分解表达式 ,然后从 Toeplitz型矩阵的特殊结构出发 ,利用上述定理的结论 ,给出了Toeplitz型矩阵的逆矩阵的一种快速三角分解算法 ,算法所需运算量为 O( mn2 ) .最后 ,数值计算表明该算法的可靠性 .     

非对称线性代数方程组的块向量算法

预条件广义共轭余量法并行和向量计算的关键是预条件计算是否可并行和向量计算，我们利用分而治之的原则，构造了一处块预条件矩阵Ｍ，这里的矩阵Ｍ是通过对线性代数方程组Ａｘ＝ｆ的矩阵Ａ进行块分解，在块分解中利用近似逆技术。这样分解形成的预条件矩阵Ｍ在迭代计算时，可向量或并行计算。     

求解块三对角方程组的新算法

根据块三对角矩阵的特殊分解,给出了求解块三对角方程组的新算法.该算法含有可以选择的参数矩阵,适当选择这些参数矩阵,可以使得计算精度较著名的追赶法高,甚至当追赶法失效时,由该算法仍可得到一定精度的解.     

Self-Adaptive Extrapolated Gauss-Seidel Iterative Methods

In this paper, we consider a self-adaptive extrapolated Gauss-Seidel method for solving the Hermitian positive definite linear systems. Based on optimization models, self-adaptive optimal factor is given. Moreover, we prove the convergence of the self-adaptive extrapolated Gauss-Seidel method without any constraints on optimal factor. Finally, the numerical examples show that the self-adaptive extrapolated Gauss-Seidel method is effective and practical in iteration number.     

A fast algorithm for computing the smallest eigenvalue of a symmetric positive‐definite Toeplitz matrix

Recent progress in signal processing and estimation has generated considerable interest in the problem of computing the smallest eigenvalue of a symmetric positive‐definite (SPD) Toeplitz matrix. An algorithm for computing upper and lower bounds to the smallest eigenvalue of a SPD Toeplitz matrix has been recently derived (Linear Algebra Appl. 2007; DOI: 10.1016/j.laa.2007.05.008 ). The algorithm relies on the computation of the R factor of the QR factorization of the Toeplitz matrix and the inverse of R. The simultaneous computation of R and R^?1 is efficiently accomplished by the generalized Schur algorithm. In this paper, exploiting the properties of the latter algorithm, a numerical method to compute the smallest eigenvalue and the corresponding eigenvector of SPD Toeplitz matrices in an accurate way is proposed. Copyright © 2008 John Wiley & Sons, Ltd.     

SQP algorithms for solving Toeplitz matrix approximation problem

Given an n × n matrix F, we find the nearest symmetric positive semi‐definite Toeplitz matrix T to F. The problem is formulated as a non‐linear minimization problem with positive semi‐definite Toeplitz matrix as constraints. Then a computational framework is given. An algorithm with rapid convergence is obtained by l₁ Sequential Quadratic Programming (SQP) method. Copyright © 2002 John Wiley & Sons, Ltd.     

On symmetric block triangular splitting iteration method for a class of complex symmetric system of linear equations

For solving a class of complex symmetric linear system, we first transform the system into a block two-by-two real formulation and construct a symmetric block triangular splitting (SBTS) iteration method based on two splittings. Then, eigenvalues of iterative matrix are calculated, convergence conditions with relaxation parameter are derived, and two optimal parameters are obtained. Besides, we present the optimal convergence factor and test two numerical examples to confirm theoretical results and to verify the high performances of SBTS iteration method compared with two classical methods.     

Fast algorithms for computing isogenies between elliptic curves

We survey algorithms for computing isogenies between elliptic curves defined over a field of characteristic either 0 or a large prime. We introduce a new algorithm that computes an isogeny of degree ( different from the characteristic) in time quasi-linear with respect to . This is based in particular on fast algorithms for power series expansion of the Weierstrass -function and related functions.