The core inverse and constrained matrix approximation problem

Abstract

Abstract In this article, we study the constrained matrix approximation problem in the Frobenius norm by using the core inverse: | | M x − b | | F = min subject to x ∈ ℛ ( M ) , ||Mx-b|{|}_{F}=\hspace{.25em}\min \hspace{1em}\text{subject}\hspace{.25em}\text{to}\hspace{1em}x\in {\mathcal R} (M), where M ∈ ℂ n CM M\in {{\mathbb{C}}}_{n}^{\text{CM}} . We get the unique solution to the problem, provide two Cramer’s rules for the unique solution and establish two new expressions for the core inverse.