摘要
本文研究了Sylvester复矩阵方程A_1Z+ZB_1=c_1的广义自反最佳逼近解.利用复合最速下降法,提出了一种的迭代算法.不论矩阵方程A_1Z+ZB_1=C_1是否相容,对于任给初始广义自反矩阵Z_0,该算法都可以计算出其广义自反的最佳逼近解.最后,通过两个数值例子,验证了该算法的可行性.
In this paper, we present an iterative algorithm to calculate the optimal approximation solutions of the Sylvester complex matrix equations A1Z + ZB1 = C1 over generalized reflexive (anti-reflexive) matrices by using the hybrid steepest descent method. Whether matrix equations A1Z + ZB1 = C1 are consistent or not, for arbitrary initial reflexive (anti-reflexive) matrix Z0, the given algorithm can be used to compute the reflexive (anti-reflexive) optimal approximation solutions. The effectiveness of the proposed algorithm is verified by two numerical examples.
出处
《数学杂志》
CSCD
北大核心
2014年第5期968-976,共9页
Journal of Mathematics
基金
安徽省教育厅自然科学基金资助(KJ2011B119)