Extension of block matrix representation of the geometric mean
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To extend the well-known extremal characterization of the geometric mean of two $n \times n$ positive definite matrices $A$ and $B$, we solve the following problem: \begin{equation*} \max \Bigg\{ X:X=X^*,~ \begin{pmatrix} A & V & X \\ V & B & W \\ X & W & C \end{pmatrix} \geq 0 \Bigg \}. \end{equation*} We find an explicit expression of the maximum value with respect to the matrix geometric mean of Schur complements.
Abstract
To extend the well-known extremal characterization of the geometric mean of two $n \times n$ positive definite matrices $A$ and $B$, we solve the following problem: \begin{equation*} \max \Bigg\{ X:X=X^*,~ \begin{pmatrix} A & V & X \\ V & B & W \\ X & W & C \end{pmatrix} \geq 0 \Bigg \}. \end{equation*} We find an explicit expression of the maximum value with respect to the matrix geometric mean of Schur complements.
참고문헌 (16)
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