周期Sylvester矩阵方程的迭代解

Zebin Chen, Xuesong Chen
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引用次数: 0

摘要

我们提出了一种基于梯度的多迭代因子(MGI)迭代算法,用于寻找Sylvester离散周期矩阵方程AjXj + Xj+1Bj = Cj(j = 1,2,⋯T)的解。证明了周期矩阵方程的精确解可以用MGI方法收敛于任何初始矩阵。然后,研究了单迭代因子梯度迭代算法的最优收敛速度。然后比较了两种算法的收敛速度,发现当选择合适的收敛因子μj时,MGI算法比SGI算法更快。最后给出了数值算例,验证了MGI在速度和迭代步骤上都优于SGI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Iterative Solutions of Periodic Sylvester Matrix Equations
We propose a gradient based iterative algorithm with multiple iterative factors (MGI) to find the solutions of the Sylvester discrete-time periodic matrix equations AjXj + Xj+1Bj = Cj(j = 1, 2,⋯, T ). It is proved that the exact solution of the periodic matrix equations can be converged by the MGI method for any initial matrices. Then, we study the optimal convergence rate of gradient based iterative algorithm with single iterative factor (SGI). Nextly, we compare the convergence rate of the two algorithms, and find that MGI is faster than SGI when the appropriate convergence factors μj are selected. Finally, a numerical example is given to verify that MGI is superior to SGI in both speed and iterative steps.
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