体上的矩阵方程AX—XB=C与AX±XB=±C

设Ｆ和Ω分别是一个任意的体和一个具有对合反自同构的有限维中心代数且ｃｈａｒΩ≠２．本研究体上的下列矩阵方程：ＡＸ－ＸＢ＝Ｃ，（１）ＡＸ－ＸＢ＝Ｃ，（２）ＡＸ＋ＸＢ＝－Ｃ（３）分别给出了在Ω上（１）有一般解，（２）自共轭解及（３）有斜自共轭解的充要条件，并将Ｗ．Ｅ．Ｒｏｔｈ的相似定理推广到了任意的体Ｆ上。     

关于正定矩阵的几个问题

本文推广了文［１］的主要定理，给出了用低阶矩阵判定高阶矩阵正定的判定定理，同时给出了矩阵方程ＡＸ＝Ｂ的反问题在正定矩阵类中解存在的充要条件及解的一般形式．     

任意体上的矩阵方程［X_（nn）A_（ns），X_（nn）B_（nt）］＝［A_

本文研究了任意体上的矩阵方程［Ｘ（ｎｎ）Ａ（ｎｓ），Ｘ（ｎｎ）Ｂ（ｎｔ）］＝［Ａ（ｎｓ），０］（１）给出了（１）相容的充要条件、通解的表达式、解的性质及其实用解法．     

关于体上矩阵方程A_（mn）X_（ns）＝B_（ms）之解的注记

本文改进了文［１］的结果，利用体上矩阵的初等行和列变换，给出了任意体上的矩阵方程ＡｍｓＸａｓ＝Ｂｍｓ的一种更为实用的简便解法。     

关于矩阵方程AXB=C

关于矩阵方程ＡＸＢ＝Ｃ丁永臻（胜利油田师专数学系２５７０９７）文［１］给出了矩阵方程ＡＸＢ＝Ｃ有解和有唯一解的一个充要条件．本文借助于近代数学常用的矩阵广义逆、直积和拉直化运算的概念及性质详细讨论矩阵方程ＡＸＢ＝Ｃ解的一般理论，包括解的存在性、唯一性...     

求解线性矩阵方程的初等变换法

求解线性矩阵方程的初等变换法杨兴东（南京气象学院基科系，南京２１００４４）杨兴洲（南京大学成人教育学院，南京２１００９３）文［１］给出了线性矩阵方程ＡＸＢ＝Ｃ有解的简单判别法则，本文则应用初等变换，给出矩阵方程ＡＸＢ＝Ｃ（１）的简便解法．引理１［２］...     

Roth定理在任意体上的推广

本文给出了任意体上的矩阵方程ＡＸ—ＹＢ＝Ｃ相容的两个充要条件，并给出了其一般解的表达式，从而推广了域上的Ｗ．Ｅ．Ｒｏｔｈ定理．     

环上矩阵方程AXB＋CYD=E的可解性

设Ｒ为一个含幺环，应用矩阵的｛１，２｝－逆（存在的前提下），本文得到Ｒ上矩阵方程ＡＸＢ＋ＣＹＤ＝Ｅ有解的充要条件以及一般解的公式，并且推广了著名的Ｒｏｔｈ等价定理。     

四元数矩阵方程∑A~iXB_i=E

设ＨＦ为域Ｆ上广义四元数可除代数，其中ｃｈａｒＦ≠２．应用伴随矩阵与矩阵表示方法，本文得到ＨＦ上矩阵方程∑ｋｉ＝０ＡｉＸＢｉ＝Ｅ有解或有唯一解的几个充要条件，并且给出了几个解的公式．     

利用初等变换求解线性矩阵方程

本文给出了一般线性矩阵方程ＡｍｎＸｎｓ＝Ｂｍｓ，ＸｍｎＡｎｓ＝Ｂｍｓ，ＡｍｎＸｎｓＢｓｔ＝Ｃｍｔ的解的结构定理，并介绍了一种利用初等变换求解上述三类线性矩阵方程的方法．     

一类四元数矩阵三次方程的可解性(英文)

确立了某类分块矩阵[M（₁1） M₁₂ XM₂₁ Y M₂₃Z M₃₂ M₃₃]的最大秩公式,其中,X,Y和Z是三个受限于四元数线性矩阵方程A₁X=C₁,XB₁=C₂,A₂Y=D₁,YB₂=D₂,A₃Z=E₁,ZB₃=E₂的变量矩阵.作为该公式的一项应用,我们推导出上述矩阵方程解集等同于某类四元数三次矩阵方程组A₁X=C₁,XB₁=C₂,A₂Y=D₁,YB₂=D₂,A₃Z=E₁,ZB₃=E₂,XYZ=J解集的条件.     

线性流形上矩阵的条件最佳逼近

设Ai,Bi,Gi为给定的矩阵,i＝1,2,S为||A1XB1－C1||2F＋||A2XB2－C2||2F＝min的解集,在给定矩阵X0的条件下,求X∈S;使得本文利用[6]的结果给出了X的表达式．     

Cartan矩阵的分解和Brauer特征标次数猜想

设G为有限群,N是G的正规子群.记J=J(F[N])为F[N]的Jacobson根,I=Ann(J)={α∈F[G]|Jα=0}为J在F[G]中的零化子.本文主要研究了,根据F[G/N]和F[G]/I的Cartan矩阵,分解F[G]的Cartan矩阵.这种分解在Cartan不变量和G的合成因子之间建立了一些联系.本文指出N中p-亏零块的存在性依赖于Cartan不变量或者I在F[G]中的性质,证明了Cartan矩阵的分解部分地依赖于B所覆盖的N中的块的性质.本文研究了b为N上的块且l(b)=1时,覆盖b的G中的块B的性质.在两类情形下,本文证明了块代数上关于Brauer特征标次数的猜想成立,涵盖了Holm和Willems研究的某些情形.进而对Holm和Willems提出的问题给出了肯定的回答.另外,本文还给出了Cartan不变量的一些其它结果.     

An equivalence canonical form of a matrix triplet over an arbitrary division ring with applications

We in this paper give a decomposition concerning the general matrix triplet over an arbitrary divisionring F with the same row or column numbers. We also design a practical algorithm for the decomposition of thematrix triplet. As applications, we present necessary and suficient conditions for the existence of the generalsolutions to the system of matrix equations DXA = C1, EXB = C2, F XC = C3 and the matrix equation AXD + BY E + CZF = Gover F. We give the expressions of the general solutions to the system a...     

The Metapositive Definite Self－Conjugate Solution of the Matrix Equation AXB＝C over a Skew Field

ＴｈｅＭｅｔａｐｏｓｉｔｉｖｅＤｅｆｉｎｉｔｅＳｅｌｆ－ＣｏｎｊｕｇａｔｅＳｏｌｕｔｉｏｎｏｆｔｈｅＭａｔｒｉｘＥｑｕａｔｉｏｎＡＸＢ＝Ｃｏｖｅｒ　ａ　Ｓｋｅｗ　ＦｉｅｌｄＷａｎｇＱｉｎｇｗｅｎ（王卿文）（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈ．，Ｃｈａｎ...     

BRILL－NOETHER MATRIX FOR RANK TWO VECTOR BUNDLES

Lei X be an arbitrary smooth irreducible complex projective curve, E (?) X a rank two vector bundle generated by its sections. The author first represents E as a triple {D1,D2,f}, where D1 , D2 are two effective divisors with d = deg(D1) + deg(D2), and f ∈ H0(X, [D1] |D2) is a collection of polynomials. E is the extension of [D2] by [D1] which is determined by f. By using f and the Brill-Noether matrix of D1 + D2, the author constructs a 2g X d matrix WE whose zero space gives Im{H0(X,[D1]) (?) H0(X, [D1] |D1)}(?)Im{H0(X, E) (?) H0(X,[D2]) (?) H0(X,[D2] |D2)}. From this and H0(X,E) = H0(X, [D1]) (?) Im{H0(X, E) (?) H0(X, [D2])}, it is got in particular that dimH0(X, E) = deg(E) - rank(WE) + 2.     

四元数体上一类矩阵方程的极小范数最小二乘解

借助于四元数体上自共轭矩阵的奇异值分解,给出了四元数矩阵方程AX＋XB＋CXD=F的极小范数最小二乘解.同时,在有解的条件下给出了Hermite最小二乘解及其通解的表达形式.     

矩阵方程X＋AXB＝C与线性流形上的矩阵最佳逼近

该文给出了矩阵方程Ｘ＋ＡＸＢ＝Ｃ存在唯一解的充分必要条件和解的表达式,该公式只是Ａ,Ｂ,Ｃ的多项式,利用该结果,解决了Ａ１ＸＢ１－Ｃ的解的表达式问题．     

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.