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A gradient-based iterative algorithm for generalized coupled Sylvester matrix equations over generalized centro-symmetric matrices

机译:广义中心对称矩阵上广义耦合Sylvester矩阵方程的基于梯度的迭代算法

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摘要

An n×n real matrix P is said to be a symmetric orthogonal matrix if P = P~(-1) = P~T. An n×n real matrix X is called a generalized centro-symmetric matrix with respect to P, if X = PXP. It is obvious that every n×n matrix is also a generalized centro-symmetric matrix with respect to I (identity matrix). In the present paper, we propose a gradient-based iterative algorithm to solve the generalized coupled Sylvester matrix equations A_1X_1B_1 + C_1X_2D_1 = E_1, A_2X_1B_2 + C_2X_2D_2 = E_2, over the generalized centro-symmetric matrix pair (X_1,X_2). It is proved that the iterative method is always convergent for any initial generalized centro-symmetric matrix pair (X_1 (I), X_2(I)). Finally, a numerical example is discussed to illustrate the results.
机译:如果P = P〜(-1)= P〜T,则称n×n实矩阵P为对称正交矩阵。如果X = PXP,则将n×n实矩阵X称为相对于P的广义中心对称矩阵。显然,每个n×n矩阵都是关于I(恒等矩阵)的广义中心对称矩阵。在本文中,我们提出了一种基于梯度的迭代算法来求解广义中心对称矩阵对(X_1,X_2)上的广义耦合Sylvester矩阵方程A_1X_1B_1 + C_1X_2D_1 = E_1,A_2X_1B_2 + C_2X_2D_2 = E_2。证明了迭代方法对于任何初始的广义中心对称矩阵对(X_1(I),X_2(I))总是收敛的。最后,讨论了一个数值示例来说明结果。

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