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Inequalities for norms of different versions of the geometric mean of two positive definite matrices are presented.

Functional Analysis · Mathematics 2015-02-17 Rajendra Bhatia , Priyanka Grover

The affine inverse eigenvalue problem consists of identifying a real symmetric matrix with a prescribed set of eigenvalues in an affine space. Due to its ubiquity in applications, various instances of the problem have been widely studied in…

Optimization and Control · Mathematics 2019-11-07 Utkan Candogan , Yong Sheng Soh , Venkat Chandrasekaran

In this paper, we propose some new semidefinite relaxations for a class of nonconvex complex quadratic programming problems, which widely appear in the areas of signal processing and power system. By deriving new valid constraints to the…

Optimization and Control · Mathematics 2023-05-18 Yingzhe Xu , Cheng Lu , Zhibin Deng , Ya-Feng Liu

To provide generalized solutions if a given problem admits no actual solution is an important task in mathematics and the natural sciences. It has a rich history dating back to the early 19th century when Carl Friedrich Gauss developed the…

Functional Analysis · Mathematics 2011-02-09 Heinz H. Bauschke , Xianfu Wang , Calvin J. S. Wylie

Often in mathematics it is useful to summarize a multivariate phenomenon with a single number and in fact, the determinant -- which is represented by det -- is one of the simplest cases. In fact, this number it is defined only for square…

Commutative Algebra · Mathematics 2009-09-17 R. S. Costas-Santos

Nonlinear matrix equations arise in many practical contexts related to control theory, dynamical programming and finite element methods for solving some partial differential equations. In most of these applications, it is needed to compute…

Numerical Analysis · Mathematics 2014-10-22 Negin Bagherpour , Nezam Mahdavi-Amiri

The main goal of this paper is to discuss the recent advancements of operator means for accretive matrices in a more general setting. In particular, we present the general form governing the well established definition of geometric mean,…

Functional Analysis · Mathematics 2021-04-16 Yassine Bedrani , Fuad Kittaneh , Mohammed Sababheh

We obtain generalisations of some inequalities for positive unital linear maps on matrix algebra. This also provides several positive semidefinite matrices and we get some old and new inequalities involving the eigenvalues of a Hermitian…

Functional Analysis · Mathematics 2016-02-16 R. Sharma , P. Devi , R. kumari

We consider a general class of random matrices whose entries are centred random variables, independent up to a symmetry constraint. We establish precise high-probability bounds on the averages of arbitrary monomials in the resolvent matrix…

Probability · Mathematics 2015-06-05 Laszlo Erdos , Antti Knowles , Horng-Tzer Yau

The geometric mean of two matrices is considered and analyzed from a computational viewpoint. Some useful theoretical properties are derived and an analysis of the conditioning is performed. Several numerical algorithms based on different…

Numerical Analysis · Mathematics 2012-01-04 Bruno Iannazzo

In this paper we consider the decomposition of positive semidefinite matrices as a sum of rank one matrices. We introduce and investigate the properties of various measures of optimality of such decompositions. For some classes of positive…

Functional Analysis · Mathematics 2022-02-03 Radu Balan , Kasso A. Okoudjou , Michael Rawson , Yang Wang , Rui Zhang

This paper is concerned with the problem of approximating the determinant of A for a large sparse symmetric positive definite matrix A. It is shown that an efficient solution of this problem is obtained by using a sparse approximate inverse…

High Energy Physics - Lattice · Physics 2007-05-23 Arnold Reusken

For operators generated by a certain class of infinite band matrices with matrix elements we establish a characterization of the resolvent set in terms of polynomial solutions of the underlying higher order finite difference equations. This…

Spectral Theory · Mathematics 2014-12-24 Andrey Osipov

The concept of Loewner (partial) order for general complex matrices is introduced. After giving the definition of arithmetic, geometric, and harmonic mean for accretive-dissipative matrices, we study their basic properties. An AM-GM-HM…

Functional Analysis · Mathematics 2022-10-18 Minghua Lin

We consider real symmetric or complex hermitian random matrices with correlated entries. We prove local laws for the resolvent and universality of the local eigenvalue statistics in the bulk of the spectrum. The correlations have fast decay…

Probability · Mathematics 2018-03-01 Oskari Ajanki , Laszlo Erdos , Torben Krüger

The multiresolution analysis of Alpert is considered. Explicit formulas for the entries in the matrix coefficients of the refinement equation are given in terms of hypergeometric functions. These entries are shown to solve generalized…

Classical Analysis and ODEs · Mathematics 2013-09-27 Jeffrey S. Geronimo , Francisco Marcellan

The averaged alternating modified reflections algorithm is a projection method for finding the closest point in the intersection of closed convex sets to a given point in a Hilbert space. In this work, we generalize the scheme so that it…

Optimization and Control · Mathematics 2024-01-03 F. J. Aragón Artacho , R. Campoy

We introduce and investigate the resolvent order, which is a binary relation on the set of firmly nonexpansive mappings. It unifies well-known orders introduced by Loewner (for positive semidefinite matrices) and by Zarantonello (for…

Functional Analysis · Mathematics 2016-06-29 Sedi Bartz , Heinz H. Bauschke , Xianfu Wang

A sum of a large-dimensional random matrix polynomial and a fixed low-rank matrix polynomial is considered. The main assumption is that the resolvent of the random polynomial converges to some deterministic limit. A formula for the limit of…

Probability · Mathematics 2022-05-23 Patryk Pagacz , Michał Wojtylak

A real symmetric matrix $M$ is completely positive semidefinite if it admits a Gram representation by (Hermitian) positive semidefinite matrices of any size $d$. The smallest such $d$ is called the (complex) completely positive semidefinite…

Optimization and Control · Mathematics 2016-10-27 Sander Gribling , David de Laat , Monique Laurent