反三角算子矩阵的Drazin可逆性及其表示

本文讨论了反三角算子矩阵■的Drazin可逆性及其Drazin逆的表达式.在CB=CAB=CA~2B,A~3=A~2条件下,采用预解式的Laurent展开方法证明了反三角算子矩阵M是Drazin可逆的,并给出M的含有A~D和(CB)~D的Drazin逆的表达式.最后给出算例,说明了结果的有效性.     

一种基于矩阵初等变换的Schmidt正交化方法

对向量组的Schmidt正交化法和合同变换法的关系进行了分析,指出Schmidt正交化法就是合同变换法中利用规范化初等变换后的一种特殊情况,由此给出一种基于矩阵初等变换的Schmidt正交化方法——Schmidt初等变换正交化法,以及这一方法在软件Matlab上实现的程序.     

四元数矩阵的广义Schmidt分解与广酉空间中向量组的广义标准正交化

推广了四元数矩阵的Schmidt分解及广酉空间中向量组的标准正交化问题，给出了实四元数矩阵分解为广酉矩阵与生对角元全正的上三角阵乘积的实用方法．     

LU分解与广义Schmidt正交化方法

利用对称内积的Schmidt正交化方法证明了各阶主子式不为零对称阵的LDLT分解.引入两个向量组关于弱内积广义正交的概念,并构造了将两组含相同个数向量的线性无关组化为广义正交组的广义Schmidt正交化方法.最后应用这一方法证明了各阶主子式不为零矩阵的LDU分解及一些相关的结果.     

M-P逆和加权M-P逆的有限迭代计算公式

本文，对于任意给定的矩阵A，我们给出了计算其M—P逆和加权M—P逆的有限迭代计算公式．根据这一迭代公式，当我们选取初始矩阵为X0=A^#，则矩阵A的加权M—P逆A^＋MN在不考虑舍入误差的情况下，可以在有限迭代的情况得到，同样当我们选取初始矩阵X0=A^＊，其M—P逆A^＋亦可以在有限迭代下获得．最后我们用数值例子检验了我们算法的正确性。     

交换环上三角矩阵模间的线性保持映射(英文)

本文研究了交换环上三角矩阵模间的线性保持问题.利用矩阵计算技巧和局部化技巧,刻画了上三角矩阵T_n(R)上分别保持立方幂等,{1}逆,{1,2}逆和群逆的所有R模自同构集合中的元素,其中R是交换环.     

一类2-Hessenberg矩阵的广义逆

在[2]中,Ikebe给出了一类下Hessenberg矩阵之逆的上三角部分的求法,从而导出三对角矩阵求逆的一种方法.文[4]中获得了计算该类Hessenberg矩阵的逆和广义逆的显式公式,由此也可得出计算三对角矩阵广义逆的方法,文[3]将[2]中的结果推广到更一般的k-Hessenberg矩阵,进而得到带状矩阵求逆的一种方法.本文研究一类实2-Hessenberg矩阵的广义逆,表明这些广义逆可由低阶三角矩阵的逆和几个简单的秩-1或     

两个幂等矩阵的组合的群逆

本文研究了当P与Q是两个复数域上的n阶幂等矩阵且满足PQP=PQ时,组合aP+bQ+cP Q+dQP+eQP Q的群逆问题,利用矩阵的分块及群逆的性质,证明了它是群逆阵,并且给出了其群逆的表达式,其中ab=0,a,b,c,d,e为复数.     

实对称矩阵对角化中正交矩阵的初等变换求法

对实对称矩阵正交对角化过程中正交矩阵的求解方法进行了研究,给出了利用初等变换求解正交矩阵的方法,该方法不需要通过特征方程求解特征值与特征向量,仅仅使用初等变换和Schmidt正交化方法.     

跳行范德蒙矩阵的三角分解

跳行范德蒙矩阵是一种重要的矩阵,在函数插值等方面有着重要的应用.根据跳行范德蒙矩阵的特殊结构,将跳行范德蒙矩阵分解为一系列下三角矩阵与一系列上三角矩阵的乘积.进一步给出了其逆矩阵分解为一系列上三角矩阵与一系列下三角矩阵的乘积的表达式.     

矩阵方程X-A~*X~(-1)A=Q的Hermite正定解及其扰动分析

考虑非线性矩阵方程X-A*X-1A=Q,其中A是n阶复矩阵,Q是n阶Hermite正定解,A*是矩阵A的共轭转置.本文证明了此方程存在唯一的正定解,并推导出此正定解的扰动边界和条件数的显式表达式.以上结果用数值例子加以说明.     

ON HERMITIAN POSITIVE DEFINITE SOLUTION OF NONLINEAR MATRIX EQUATION X＋A^＊X^-2A=Q

Based on the fixed-point theory, we study the existence and the uniqueness of the maximal Hermitian positive definite solution of the nonlinear matrix equation X＋A^＊X^-2A=Q, where Q is a square Hermitian positive definite matrix and A＊ is the conjugate transpose of the matrix A. We also demonstrate some essential properties and analyze the sensitivity of this solution. In addition, we derive computable error bounds about the approximations to the maximal Hermitian positive definite solution of the nonlinear matrix equation X＋A^＊X^-2A=Q. At last, we further generalize these results to the nonlinear matrix equation X＋A^＊X^-nA=Q, where n≥2 is a given positive integer.     

实矩阵的Hadamard积的一些性质

对于任意的n阶实矩阵A,给出了A(A*)T与A的奇异性间的关系,指出了A(A*)T的行和与列和为矩阵A的行列式|A|,最后给出了矩阵类A(A*)T与n阶方阵的一个等价类的一一对应关系.     

分块幂等矩阵中广义Schur补的幂等性

为了讨论分块幂等矩阵中使用A(1)与A(2)的广义Schur补的幂等性问题,定义了(M/D)I=D-CA(1)B和(M/A)_O=D-CA(2)B,讨论得到了(M/D)_I=D-CA(1)B与(M/A)O=D-CA(2)B具有幂等性的充要条件,并研究了一些特殊情况,推广了J K Baksalary和Zhou J H的结论.     

Backward error analysis of an inexact Arnoldi method

We investigate the behavior of Arnoldi's method for Hermitian matrices in the case of inexact vector operations. A special purpose variant of Gram Schmidt orthogonalization is introduced which computes a nearly orthogonal Krylov subspace basis and additionally implicitly provides an exactly orthogonal basis. In the second part we perform a backward error analysis and show that the exactly orthogonal basis satisfies a Krylov relation for a perturbed system matrix. The norm of the backward error is shown to be on the level of the accuracy of the vector operations. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Approximations with Real Linear Modules

Real linear approximation theory is developed further by regarding ? ⁿ as a module over the ring of circlets. By introducing a concept of orthogonality together with the respective Gram–Schmidt orthogonalization process, improved approximations upon the standard complex Hilbert space techniques follow. Related hierarchical bases are devised leading to a new family of rapidly constructible family of unitary matrices. With circlets, so-called oplets are introduced for approximation to improve the singular value decomposition of real matrices. Complex matrix approximation is also considered through finding the nearest real matrix in small rank perturbations.     

环上矩阵广义Moore-Penrose逆的存在性

讨论带有对合反自同构*有单位元的结合环R上矩阵的广义Moore-Penrose 逆,给出了环R上矩阵的广义Moore-Penrose逆存在的几个充要条件．特别,得到了环 R上矩阵A的关于M和N的广义Moore-Penrose逆存在的充要条件是A有分解A= GDH,其中D2=D,(MD)*=MD,(GD)*MGD+M(I-D)和DHN-1(DH)*+ (I-D)M-1均可逆．     

Decomposition of Matrices into Involutory Matrices and Symmetric Matrices

Let \Omega be a field, and let F denote the Frobenius matrix: $[F = \left( {\begin{array}{*{20}{c}} 0&{ - {\alpha _n}}\{{E_{n - 1}}}&\alpha \end{array}} \right)\]$ where \alpha is an n-1 dimentional vector over Q, and E_n- 1 is identity matrix over \Omega. Theorem 1. There hold two elementary decompositions of Frobenius matrix: (i) F=SJB, where S, J are two symmetric matrices, and B is an involutory matrix; (ii) F=CQD, where O is an involutory matrix, Q is an orthogonal matrix over \Omega, and D is a diagonal matrix. We use the decomposition (i) to deduce the following two theorems: Theorem 2. Every square matrix over \Omega is a product of twe symmetric matrices and one involutory matrix. Theorem 3. Every square matrix over \Omega is a product of not more than four symmetric matrices. By using the decomposition (ii), we easily verify the following Theorem 4(Wonenburger-Djokovic') . The necessary and sufficient condition that a square matrix A may be decomposed as a product of two involutory matrices is that A is nonsingular and similar to its inverse A^-1 over Q (See [2, 3]). We also use the decomosition (ii) to obtain Theorem 5. Every unimodular matrix is similar to the matrix CQB, where C, B are two involutory matrices, and Q is an orthogonal matrix over Q. As a consequence of Theorem 5. we deduce immediately the following Theorem 6 (Gustafson-Halmos-Radjavi). Every unimodular matrix may be decomposed as a product of not more than four involutory matrices (See [1] ). Finally, we use the decomposition (ii) to derive the following Thoerem 7. If the unimodular matrix A possesses one invariant factor which is not constant polynomial, or the determinant of the unimodular matrix A is I and A possesses two invariant factors with the same degree (>0), then A may be decomposed as a product of three involutory matrices. All of the proofs of the above theorems are constructive.     

Hermite-广义反Hamilton矩阵的一类反问题

给定矩阵X和B,利用矩阵的广义奇异值分解,得到了矩阵方程X~HAX=B有Hermite-广义反Hamiton解的充分必要条件及有解时解的—般表达式.用S_E表示此矩阵方程的解集合,证明了S_E中存在唯一的矩阵(?),使得(?)与给定矩阵A的差的Frobenius范数最小,并且给出了矩阵(?)的表达式;同时也证明了S_E中存在唯一的矩阵A_o,使得A_o是此矩阵方程的极小Frobenius范数Hermite-广义反Hamilton解,并且给出了矩阵A_o的表达式.