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 …

A majorization-minimization (MM) algorithm for the Karcher mean of np× p positive definite
matrices is proposed and it is gauranteed to converge linearly. Simulations show that the …

Computing the Karcher mean of symmetric positive definite matrices Page 1 Linear Algebra and
its Applications 438 (2013) 1700–1710 Contents lists available at SciVerse ScienceDirect …

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 …

The generalization of the geometric mean of positive scalars to positive definite matrices has
attracted considerable attention since the seminal work of Ando. The paper generalizes this …

It is shown that any two-variable-mean of positive matrices (studied by Kubo and Ando) can
be extended to more variables. The n-variable-mean M_n(A_1,A_2,...,A_n) is defined by a …

Here we prove the convergence of the Ando–Li–Mathias and Bini–Meini–Poloni procedures
for matrix means. Actually it is proved here that for a two-variable function which maps pairs …

The Karcher or least-squares mean has recently become an important tool for the averaging
and studying of positive definite matrices. In this paper we show that this mean extends, in its …

The Karcher or least-squares mean has recently become an important tool for the averaging
and study of positive definite matrices. In this paper, we show that this mean extends, in its …

A nonnegative symmetric matrix B has row maxima prescribed by a given vector r, if for each
index i, the maximum entry in the i th row of B equals r_i. This paper presents necessary and …