The purpose of this research is to present a novel scheme based on a quick iterative
scheme for calculating the matrix geometric mean of two Hermitian positive definite (HPD) …

Using the relation between a principal matrix square root and its inverse with the geometric
mean, we present a fast algorithm for computing the geometric mean of two Hermitian …

In this work, an iterative method is developed to find the matrix sign function. It is discussed
in detail that the method is novel in comparison to its competitors from the Padé family of …

The target of this work is to present a multiplication-based iterative method for two Hermitian
positive definite matrices to find the geometric mean. The method is constructed via the …

The geometric mean of two matrices is considered from a computational viewpoint. Several
numerical algorithms based on different properties and representations of the geometric …

The set of Hermitian positive-definite matrices plays fundamental roles in many disciplines
such as mathematics, numerical analysis, probability and statistics, engineering, and …

We propose a new algorithm to approximate the Karcher mean of N symmetric positive
definite (SDP) matrices. By" Karcher mean", we refer to the Riemannian center of mass with …

An algorithm for computing the Karcher mean of n positive definite matrices is proposed,
based on the majorization-minimization (MM) principle. The proposed MM algorithm is …

In this paper, we introduce properly-invariant diagonality measures of Hermitian positive-
definite matrices. These diagonality measures are defined as distances or divergences …

We explore the connection between two problems that have arisen independently in the
signal processing and related fields: the estimation of the geometric mean of a set of …