一四元数矩阵方程组的广义(反)反射解

该文给出了四元数矩阵方程组X_1B_1=C_1,X_2B_2=C2,A_1X_1B_3+A_2X_2B_4=C_b可解的充要条件及其通解的表达式,利用此结果建立了四元数矩阵方程组XB_a=C_a,A_bXB_b=C_b有广义(反)反射解的充要条件及其有此种解时通解的表达式.     

A System of Four Matrix Equations over von Neumann Regular Rings and Its Applications

We consider the system of four linear matrix equations A1X = C1, XB2=C2, A3XB3=C3 and A4XB4 = C4 over h, an arbitrary von Neumann regular ring with identity. A necessary and sufficient condition for the existence and the expression of the general solution to the system are derived. As applications, necessary and sufficient conditions are given for the system of matrix equations A1X = C1 and A3X=C3 to have a bisymmetric solution, the system of matrix equations A1X = C1 and A3XB3 = C3 to have a perselfconjugate solution over h with an involution and char h≠2, respectively. The representations of such solutions are also presented. Moreover, some auxiliary resultson other systems over h are obtained. The previous known results on some systems of matrix equations are special cases of the new results.     

The Real Solutions to a System of Quaternion Matrix Equations with Applications

In this article we establish necessary and sufficient conditions for the existence and the expressions of the general real solutions to the classical system of quaternion matrix equations A ₁ XB ₁ = C ₁, A ₂ XB ₂ = C ₂. Moreover, formulas of the maximal and minimal ranks of four real matrices X ₁, X ₂, X ₃, and X ₄ in solution X = X ₁ + X ₂ i + X ₃ j + X ₄ k to the system mentioned above are derived. As applications, we give necessary and sufficient conditions for the quaternion matrix equations A ₁ XB ₁ = C ₁, A ₂ XB ₂ = C ₂, A ₃ XB ₃ = C ₃ to have common real solutions. In addition, the maximal and minimal ranks of four real matrices E, F, G, and H in the common generalized inverse of A ₁ + B ₁ i + C ₁ j + D ₁ k and A ₂ + B ₂ i + C ₂ j + D ₂ k, which can be expressed as E + Fi + Gj + Hk are also presented.     

The common Re-nnd and Re-pd solutions to the matrix equations AX = C and XB = D

In this article, we consider common Re-nnd and Re-pd solutions of the matrix equations AX = C and XB = D with respect to X, where A, B, C and D are given matrices. We give necessary and sufficient conditions for the existence of common Re-nnd and Re-pd solutions to the pair of the matrix equations and derive a representation of the common Re-nnd and Re-pd solutions to these two equations when they exist. The presented examples show the advantage of the proposed approach.     

The maximal and minimal ranks of a quaternion matrix expression with applications

In this paper, we establish the formulas of the extermal ranks of the quaternion matrix expression f(X₁, X₂) = C₇ ? A₄X₁B₄ ? A₅X₂B₅ where X₁, X₂ are variant quaternion matrices subject to quaternion matrix equations A₁X₁ = C₁, A₂X₁ = C₂, A₃X₁ = C₃, X₂B₁ = C₄, X₂B₂ = C₅, X₂B₃ = C₆. As applications, we give a new necessary and sufficient condition for the existence of solutions to some systems of quaternion matrix equations. Some results can be viewed as special cases of the results of this paper.     

The common bisymmetric nonnegative definite solutions with extreme ranks and inertias to a pair of matrix equations

We in this paper consider the bisymmetric nonnegative definite solution with extremal ranks and inertias to a system of quaternion matrix equations AX = C, XB = D. We derive the extremal ranks and inertias of the common bisymmetric nonnegative definite solution to the system. The general expressions of the bisymmetric nonnegative definite solution with extremal ranks and inertias to the system mentioned above are also presented. In addition, we give a numerical example to illustrate the results of this paper.     

Some properties of submatrices in a solution to the matrix equations AX=C, XB=D

Suppose that AX=C, XB=D has a common solution and partition its solution $X=\bigl[{\fontsize{7.5}{9}\selectfont \begin{array}{cc}X_{1}&X_{2}\\X_{3}&X_{4}\end{array}}\bigr]$ . In this paper, we give some formulas for the maximal and minimal ranks of the submatrices in a solution X to matrix equations AX=C, XB=D. In addition, we investigate the uniqueness and the independence of submatrices in a solutions X to this equations.     

The solvability of two linear matrix equations

The solvability conditions of the following two linear matrix equations (i)A₁X₁B₁ +A₂X₂B₂ +A₃X₃B₃ =C,(ii) A₁XB₁ =C₁ A₂XB₂ =C₂ are established using ranks and generalized inverses of matrices. In addition, the duality of the three types of matrix equations

(iii) A ₁ X ₁ B ₁+A ₂ X ₂ B ₂+A ₃ X ₃ B ₃+A ₄ X ₄ B ₄=C, (iv) A ₁ XB ₁=C ₁ A ₂ XB ₂=C ₂ A ₃ XB ₃=C ₃ A ₄ XB ₄=C ₄, (v) AXB+CXD=E are also considered.     

一类四元数矩阵方程的循环解及其最佳逼近

本文研究了四元数体上矩阵方程XB = C 的循环解及其最佳逼近问题. 利用循环矩阵的结构表示式, 以及四元数矩阵的复分解, 得到了方程XB = C 的循环解存在条件及其通解形式; 在循环矩阵约束条件下, 给出了该方程的最小二乘解集合; 与此同时, 在最小二乘解集合中, 获得与给定四元数循环矩阵的最佳逼近解. 推广了约束矩阵方程的数值求解范围. 数值算例验证了本文算法的可行性.     

一类四元数矩阵方程的循环解及其最佳逼近

本文研究了四元数体上矩阵方程XB=C的循环解及其最佳逼近问题.利用循环矩阵的结构表示式,以及四元数矩阵的复分解,得到了方程XB=C的循环解存在条件及其通解形式;在循环矩阵约束条件下,给出了该方程的最小二乘解集合;与此同时,在最小二乘解集合中,获得与给定四元数循环矩阵的最佳逼近解.推广了约束矩阵方程的数值求解范围.数值算例验证了本文算法的可行性.     

Controllability,observability and the solution of AX - XB = C

A closed-form finite series representation of the unique solution X of the matrix equation AX ? XB=C is developed. Using this representation, the image, kernel, and rank of X are related to the controllable and unobservable subspaces of the (A, C) and (C, B) pairs respectively. Bounds on the rank of X are obtainedin terms of the dimensions of these subspaces. In the case that C has unitary rank, an exact calculation of rank X is made. The generic rank of X with A, B fixed and C generic is evaluated.     

Minimal ranks of some quaternion matrix expressions with applications

Suppose that p(X, Y) = A − BX − X^(∗)B^(∗) − CYC^(∗) and q(X, Y) = A − BX + X^(∗)B^(∗) − CYC^(∗) are quaternion matrix expressions, where A is persymmetric or perskew-symmetric. We in this paper derive the minimal rank formula of p(X, Y) with respect to pair of matrices X and Y = Y^(∗), and the minimal rank formula of q(X, Y) with respect to pair of matrices X and Y = −Y^(∗). As applications, we establish some necessary and sufficient conditions for the existence of the general (persymmetric or perskew-symmetric) solutions to some well-known linear quaternion matrix equations. The expressions are also given for the corresponding general solutions of the matrix equations when the solvability conditions are satisfied. At the same time, some useful consequences are also developed.     

Simultaneous solutions of Sylvester equations and idempotent matrices separating the joint spectrum

We investigate simultaneous solutions of the matrix Sylvester equations A_iX-XB_i=C_i,i=1,2,…,k, where {A₁,…,A_k} and {B₁,…,B_k} are k-tuples of commuting matrices of order m×m and p×p, respectively. We show that the matrix Sylvester equations have a unique solution X for every compatible k-tuple of m×p matrices {C₁,…,C_k} if and only if the joint spectra σ(A₁,…,A_k) and σ(B₁,…,B_k) are disjoint. We discuss the connection between the simultaneous solutions of Sylvester equations and related questions about idempotent matrices separating disjoint subsets of the joint spectrum, spectral mapping for the differences of commuting k-tuples, and a characterization of the joint spectrum via simultaneous solutions of systems of linear equations.     

Iterative orthogonal direction methods for Hermitian minimum norm solutions of two consistent matrix equations

The consistent conditions and the general expressions about the Hermitian solutions of the linear matrix equations AXB=C and (AX, XB)=(C, D) are studied in depth, where A, B, C and D are given matrices of suitable sizes. The Hermitian minimum F‐norm solutions are obtained for the matrix equations AXB=C and (AX, XB)=(C, D) by Moore–Penrose generalized inverse, respectively. For both matrix equations, we design iterative methods according to the fundamental idea of the classical conjugate direction method for the standard system of linear equations. Numerical results show that these iterative methods are feasible and effective in actual computations of the solutions of the above‐mentioned two matrix equations. Copyright © 2006 John Wiley & Sons, Ltd.     

The matrix equations AX = C, XB = D

For the pair of matrix equations AX = C, XB = D this paper gives common solutions of minimum possible rank and also other feasible specified ranks.     

How to use RSVD to solve the matrix equation A=BXC

Through the restricted singular value decomposition (RSVD) of the matrix triplet (C, A, B), we show in this note how to choose a variable matrix X such that the matrix pencil A ? BXC attains its maximal and minimal ranks. As applications, we show how to use the RSVD to solve the matrix equation A = BXC.     

Solutions to Operator Equations on Hilbert C*-Modules II

In this paper, we study the solvability of the operator equations A*X + X*A = C and A*XB + B*X*A = C for general adjointable operators on Hilbert C*-modules whose ranges may not be closed. Based on these results we discuss the solution to the operator equation AXB = C, and obtain some necessary and sufficient conditions for the existence of a real positive solution, of a solution X with B*(X* + X)B ≥ 0, and of a solution X with B*XB ≥ 0. Furthermore in the special case that R(B) í [`(R(A*))]{R(B)\subseteq\overline{R(A*)}} we obtain a necessary and sufficient condition for the existence of a positive solution to the equation AXB = C. The above results generalize some recent results concerning the equations for operators with closed ranges.     

The generalized quaternion matrix equation AXB+CX⋆D=E

In this paper, we discuss the generalized quaternion matrix equation AXB+CX^⋆D=E, where X^⋆ is one of X, X^*, the η-conjugate or the η-conjugate transpose of X with η∈{i,j,k}. Two new real representations of a generalized quaternion matrix are proposed. By using this method, the criteria for the existence and uniqueness of solutions to the mentioned matrix equation as well as the existence of X=± X^⋆ solutions to the generalized quaternion matrix equation AXB+CXD=E are derived in a unified way.     

Cauchy-type determinants and integrable systems

It is well known that the Sylvester matrix equation AX + XB = C has a unique solution X if and only if 0 ∉ spec(A) + spec(B). The main result of the present article are explicit formulas for the determinant of X in the case that C is one-dimensional. For diagonal matrices A, B, we reobtain a classical result by Cauchy as a special case.The formulas we obtain are a cornerstone in the asymptotic classification of multiple pole solutions to integrable systems like the sine-Gordon equation and the Toda lattice. We will provide a concise introduction to the background from soliton theory, an operator theoretic approach originating from work of Marchenko and Carl, and discuss examples for the application of the main results.