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Abstract

This paper presents a unified treatment of first-order linear matrix equations (FLMEs) with pure delay in both continuous and discrete time, under the general setting of noncommutative coefficient matrices. In the continuous-time framework, we consider delayed matrix differential equations of the form \[ \dot{X}(\vartheta) = A_0 X(\vartheta-\sigma) + X(\vartheta-\sigma) A_1 + G(\vartheta), \quad \vartheta \geq 0, \] where \(A_0, A_1 \in \mathbb{R}^{d \times d}\) satisfy \(A_0 A_1 \neq A_1 A_0\), \(G(\vartheta)\) is a prescribed matrix function, and \(\sigma >0\) denotes the delay. We derive explicit representations of the solution for initial data \(X(\vartheta) = \Psi(\vartheta)\), \(\vartheta \in [-\sigma,0]\), highlighting the structural impact of noncommutativity. For the discrete-time analogue, the system \[ \Delta X(u) = A_0 X(u-m) + X(u-m) A_1 + G(u) \] is analyzed using recursively defined auxiliary matrices \(Q_u\) and a fundamental matrix function \(Z(u)\), yielding closed-form solutions for both homogeneous and non-homogeneous cases. These results extend classical representations for commutative systems to the noncommutative setting. Collectively, continuous and discrete analyzes provide a comprehensive framework for understanding delayed linear matrix dynamics, with potential applications in control theory, signal processing, and iterative learning.