Finite iterative algorithms for solving generalized coupled Sylvester systems – Part I: One-sided and generalized coupled Sylvester matrix equations over generalized reflexive solutions

AbstractThe generalized coupled Sylvester systems play a fundamental role in wide applications in several areas, such as stability theory, control theory, perturbation analysis, and some other fields of pure and applied mathematics. The iterative method is an important way to solve the generalized coupled Sylvester systems. In this two-part article, finite iterative methods are proposed for solving one-sided (or two-sided) and generalized coupled Sylvester matrix equations and the corresponding optimal approximation problem over generalized reflexive solutions (or reflexive solutions). In part I, an iterative algorithm is constructed to solve one-sided and coupled Sylvester matrix equations (AY−ZB,CY−ZD)=(E,F) over generalized reflexive matrices Y and Z. When the matrix equations are consistent, for any initial generalized reflexive matrix pair [Y1,Z1], the generalized reflexive solutions can be obtained by the iterative algorithm within finite iterative steps in the absence of round-off errors, and the least Frobenius norm generalized reflexive solution pair can be obtained by choosing a special kind of initial matrix pair. The unique optimal approximation generalized reflexive solution pair [Y^,Z^] to a given matrix pair [Y0,Z0] in Frobenius norm can be derived by finding the least-norm generalized reflexive solution pair [Y∼∗,Z∼∗] of two new corresponding generalized coupled Sylvester matrix equations (AY∼-Z∼B,CY∼-Z∼D)=(E∼,F∼), where E∼=E-AY0+Z0B,F∼=F-CY0+Z0D. Several numerical examples are given to show the effectiveness of the presented iterative algorithm

LSMR Iterative Method for General Coupled Matrix Equations

By extending the idea of LSMR method, we present an iterative method to solve the general coupled matrix equations ∑k=1qAikXkBik=Ci, i=1,2,…,p, (including the generalized (coupled) Lyapunov and Sylvester matrix equations as special cases) over some constrained matrix groups (X1,X2,…,Xq), such as symmetric, generalized bisymmetric, and (R,S)-symmetric matrix groups. By this iterative method, for any initial matrix group (X1(0),X2(0),…,Xq(0)), a solution group (X1*,X2*,…,Xq*) can be obtained within finite iteration steps in absence of round-off errors, and the minimum Frobenius norm solution or the minimum Frobenius norm least-squares solution group can be derived when an appropriate initial iterative matrix group is chosen. In addition, the optimal approximation solution group to a given matrix group (X¯1,X¯2,…,X¯q) in the Frobenius norm can be obtained by finding the least Frobenius norm solution group of new general coupled matrix equations. Finally, numerical examples are given to illustrate the effectiveness of the presented method

(R, S) conjugate solution to coupled Sylvester complex matrix equations with conjugate of two unknowns

In this work, we are concerned with (R, S) – conjugate solutions to coupled Sylvester complex matrix equations with conjugate of two unknowns. When the considered two matrix equations are consistent, it is demonstrated that the solutions can be obtained by utilizing this iterative algorithm for any initial arbitrary (R,S) – conjugate matrices V1,W1. A necessary and sufficient condition is established to guarantee that the proposed method converges to the (R,S) – conjugate solutions. Finally, two numerical examples are provided to demonstrate the efficiency of the described iterative technique

The Least Squares Hermitian (Anti)reflexive Solution with the Least Norm to Matrix Equation A

For a given generalized reflection matrix J, that is, JH=J, J2=I, where JH is the conjugate transpose matrix of J, a matrix A∈Cn×n is called a Hermitian (anti)reflexive matrix with respect to J if AH=A and A=±JAJ. By using the Kronecker product, we derive the explicit expression of least squares Hermitian (anti)reflexive solution with the least norm to matrix equation AXB=C over complex field

Gradient Based Iterative Algorithm to Solve General Coupled Discrete-Time Periodic Matrix Equations over Generalized Reflexive Matrices

The discrete-time periodic matrix equations are encountered in periodic state feedback problems and model reduction of periodic descriptor systems. The aim of this paper is to compute the generalized reflexive solutions of the general coupled discrete-time periodic matrix equations. We introduce a gradient-based iterative (GI) algorithm for finding the generalized reflexive solutions of the general coupled discretetime periodic matrix equations. It is shown that the introduced GI algorithm always converges to the generalized reflexive solutions for any initial generalized reflexive matrices. Finally, two numerical examples are investigated to confirm the efficiency of GI algorithm