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Gradient-based iterative algorithm for solving the generalized coupled Sylvester-transpose and conjugate matrix equations over reflexive (anti-reflexive) matrices

机译:自反(反自反)矩阵上广义广义Sylvester-Transpose和共轭矩阵方程组的基于梯度的迭代算法

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Linear matrix equations play an important role in many areas, such as control theory, system theory, stability theory and some other fields of pure and applied mathematics. In the present paper, we consider the generalized coupled Sylvester-transpose and conjugate matrix equations T_v(X) = F_v, v = 1,2, ...,N, where X = (X_1, X_2, ...,X_p) is a group of unknown matrices and for v = 1,2, ...,N, T_v(X) = ∑_(i = 1)~p ∑_(μ = 1)~(s_1) A_(viμ)X_iB_(viμ) + ∑_(μ = 1)~(s_2) C_(viμ)X_i~TD_(viμ) + ∑_(μ - 1)~(s_3) M_(viμ)X_iN_(viμ) + ∑_(μ = 1)~(s_4) H_(viμ)X_i~HG_(viμ), in which A_(viμ), B_(viμ), C_(viμ), D_(viμ), M_(viμ), N_(viμ), H_(viμ), G_(viμ) and F_v are given matrices with suitable dimensions defined over complex number field. By using the hierarchical identification principle, an iterative algorithm is proposed for solving the above coupled linear matrix equations over the group of reflexive (anti-reflexive) matrices. Meanwhile, sufficient conditions are established which guarantee the convergence of the presented algorithm. Finally, some numerical examples are given to demonstrate the validity of our theoretical results and the efficiency of the algorithm for solving the mentioned coupled linear matrix equations.
机译:线性矩阵方程在许多领域都扮演着重要角色,例如控制理论,系统理论,稳定性理论以及其他一些纯数学和应用数学领域。在本文中,我们考虑广义耦合的Sylvester转置和共轭矩阵方程T_v(X)= F_v,v = 1,2,...,N,其中X =(X_1,X_2,...,X_p)是一组未知矩阵,对于v = 1,2,...,N,T_v(X)= ∑_(i = 1)〜p ∑_(μ= 1)〜(s_1)A_(viμ)X_iB_ (viμ)+ ∑_(μ= 1)〜(s_2)C_(viμ)X_i〜TD_(viμ)+ ∑_(μ-1)〜(s_3)M_(viμ)X_iN_(viμ)+ ∑_(μ = 1)〜(s_4)H_(viμ)X_i〜HG_(viμ),其中A_(viμ),B_(viμ),C_(viμ),D_(viμ),M_(viμ),N_(viμ),给定H_(viμ),G_(viμ)和F_v矩阵,并在复数字段上定义了合适的维数。通过使用层次识别原理,提出了一种迭代算法,用于求解自反矩阵(反自反矩阵)上的上述耦合线性矩阵方程。同时,建立了足以保证所提出算法收敛的条件。最后,给出了一些数值算例,以证明我们的理论结果的有效性以及该算法求解上述耦合线性矩阵方程的有效性。

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