Systems of coupled generalized Sylvester matrix equations

This paper studies some systems of coupled generalized Sylvester matrix equations. We present some necessary and sufficient conditions for the solvability to these systems. We give the expressions of the general solutions to the systems when their solvability conditions are satisfied.     

BCR method for solving generalized coupled Sylvester equations over centrosymmetric or anti-centrosymmetric matrix

This paper introduces another version of biconjugate residual method (BCR) for solving the generalized coupled Sylvester matrix equations over centrosymmetric or anti-centrosymmetric matrix. We prove this version of BCR algorithm can find the centrosymmetric solution group of the generalized coupled matrix equations for any initial matrix group within finite steps in the absence of round-off errors. Furthermore, a method is provided for choosing the initial matrices to obtain the least norm solution of the problem. At last, some numerical examples are provided to illustrate the efficiency and validity of methods we have proposed.     

An iterative algorithm for solving a pair of matrix equations over generalized centro-symmetric matrices

A matrix is said to be a symmetric orthogonal matrix if . A matrix is said to be generalized centro-symmetric (generalized central anti-symmetric) with respect to P, if A=PAP (A=−PAP). The generalized centro-symmetric matrices have wide applications in information theory, linear estimate theory and numerical analysis. In this paper, we propose a new iterative algorithm to compute a generalized centro-symmetric solution of the linear matrix equations . We show, when the matrix equations are consistent over generalized centro-symmetric matrix Y, for any initial generalized centro-symmetric matrix Y₁, the sequence {Y_k} generated by the introduced algorithm converges to a generalized centro-symmetric solution of matrix equations . The least Frobenius norm generalized centro-symmetric solution can be derived when a special initial generalized centro-symmetric matrix is chosen. Furthermore, the optimal approximation generalized centro-symmetric solution to a given generalized centro-symmetric matrix can be derived. Several numerical examples are given to show the efficiency of the presented method.     

Gradient-based iterative algorithms for generalized coupled Sylvester-conjugate matrix equations

By applying the hierarchical identification principle, the gradient-based iterative algorithm is suggested to solve a class of complex matrix equations. With the real representation of a complex matrix as a tool, the sufficient and necessary conditions for the convergence factor are determined to guarantee that the iterative solutions given by the proposed algorithm converge to the exact solution for any initial matrices. Also, we solve the problem which is proposed by Wu et al. (2010). Finally, some numerical examples are provided to illustrate the effectiveness of the proposed algorithms and testify the conclusions suggested in this paper.     

A note on combined generalized Sylvester matrix equations

The solution of two combined generalized Sylvester matrix equations is studied. It is first shown that the two combined generalized Sylvester matrix equations can be converted into a normal Sylvester matrix equation through extension, and then with the help of a result for solution to normal Sylvester matrix equations, the complete solution to the two combined generalized Sylvester matrix equations is derived. A demonstrative example shows the effect of the proposed approach.     

On the generalized Sylvester mapping and matrix equations

General parametric solution to a family of generalized Sylvester matrix equations arising in linear system theory is presented by using the so-called generalized Sylvester mapping which has some elegant properties. The solution consists of some polynomial matrices satisfying certain conditions and a parametric matrix representing the degree of freedom in the solution. The results provide great convenience to the computation and analysis of the solutions to this family of equations, and can perform important functions in many analysis and design problems in linear system theory. It is also expected that this so-called generalized Sylvester mapping tool may have some other applications in control system theory.     

Solving genus zero Diophantine equations over number fields

Let K be a number field and F(X,Y) an absolutely irreducible polynomial of K[X,Y] such that the algebraic curve defined by the equation F(X,Y)=0 is rational. In this paper we present practical algorithms for the determination of all solutions of the Diophantine equation F(X,Y)=0 in algebraic integers of K.     

Efficient iterative solutions to general coupled matrix equations

Linear matrix equations are encountered in many systems and control applications.In this paper,we consider the general coupled matrix equations（including the generalized coupled Sylvester matrix equations as a special case）l t=1EstYtFst = Gs,s = 1,2,···,l over the generalized reflexive matrix group（Y1,Y2,···,Yl）.We derive an efcient gradient-iterative（GI） algorithm for fnding the generalized reflexive solution group of the general coupled matrix equations.Convergence analysis indicates that the algorithm always converges to the generalized reflexive solution group for any initial generalized reflexive matrix group（Y1（1）,Y2（1）,···,Yl（1））.Finally,numerical results are presented to test and illustrate the performance of the algorithm in terms of convergence,accuracy as well as the efciency.     

Solving time-invariant differential matrix Riccati equations using GPGPU computing

Differential matrix Riccati equations (DMREs) enable to model many physical systems appearing in different branches of science, in some cases, involving very large problem sizes. In this paper, we propose an adaptive algorithm for time-invariant DMREs that uses a piecewise-linearized approach based on the Padé approximation of the matrix exponential. The algorithm designed is based upon intensive use of matrix products and linear system solutions so we can seize the large computational capability that modern graphics processing units (GPUs) have on these types of operations using CUBLAS and CULATOOLS libraries (general purpose GPU), which are efficient implementations of BLAS and LAPACK libraries, respectively, for NVIDIA \(\copyright \) GPUs. A thorough analysis showed that some parts of the algorithm proposed can be carried out in parallel, thus allowing to leverage the two GPUs available in many current compute nodes. Besides, our algorithm can be used by any interested researcher through a friendly MATLAB \(\copyright \) interface.     

Solving polynomial nonlinear matrix equations by a linearization method

This paper deals with some modification of a matrix linearization method. The scheme proposed makes it possible to find tuples of solutions for systems of polynomial nonlinear equations defined on a commutative matrix ring. The matrix linearization method reduces an initial polynomial nonlinear problem to a linear one with respect to matrices of solutions. Then, the method of elimination of unknowns is used to obtain a generalized eigenvalue problem. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 60–69, May–June 2006.     

Discrete generalized algebraic Riccati equations and polynomial matrix factorization

This paper presents an algorithm for solving discrete generalized algebraic Riccati equations with the help of an orthogonal projector. A generalization of the procedure of forming and correcting the orthogonal projector is considered and also that of correcting the proper solution by the Newton-Raphson scheme. The possibility to use the discrete generalized Riccati equations for polynomial matrix factorization with respect to the unit circle is demonstrated. A numerical example is given.     

Solving a class of higher-order equations over a group structure

This paper proposes a new symbolic method for solving a class of higher-order equations with an unknown function over the complex domain. Our method exploits the closure property of group structure (for functions) in order to allow an equivalent system of equations to be expressed and solved in the first-order setting.Our work is an initial step towards the relatively unexplored realm of higher-order constraint solving, in general; and higher-order equational solving, in particular. We shall provide some theoretical background for the proposed method, and also prototype an implementation under Mathematica.     

广义预测控制中Diophantine矩阵多项式方程的显式解

直接利用被控对象的离散差分方程推导出多变量广义预测控制中Diophantine矩阵多项式方程的显式解,从而避免了其递推求解或迭代求解,使广义预测控制的应用更加方便．     

Developing Bi-CG and Bi-CR methods to solve generalized Sylvester-transpose matrix equations

The bi-conjugate gradients(Bi-CG)and bi-conjugate residual(Bi-CR)methods are powerful tools for solving nonsymmetric linear systems Ax=b.By using Kronecker product and vectorization operator,this paper develops the Bi-CG and Bi-CR methods for the solution of the generalized Sylvester-transpose matrix equationp i=1(Ai X Bi+Ci XTDi)=E(including Lyapunov,Sylvester and Sylvester-transpose matrix equations as special cases).Numerical results validate that the proposed algorithms are much more efcient than some existing algorithms.     

Solutions to the generalized Sylvester matrix equations by a singular value decomposition

In this paper,solutions to the generalized Sylvester matrix equations AX-XF=BY and MXN-X=TY with A,M∈Rn×n,B,T∈Rn×n,F,N∈Rp×p and the matrices N,F being in companion form,are established by a singular value decomposition of a matrix with dimensions n×(n pr).The algorithm proposed in this paper for the euqation AX-XF=BY does not require the controllability of matrix pair(A,B)andthe restriction that A,F do not have common eigenvalues.Since singular value decomposition is adopted,the algorithm is numerically stable and may provide great convenience to the computation of the solution to these equations,and can perform important functions in many design problems in control systems theory.