AbstractWe define a new average – termed the resolvent average – for positive semidefinite matrices. For positive definite matrices, the resolvent average enjoys self-duality and it interpolates between the harmonic and the arithmetic averages, which it approaches when taking appropriate limits. We compare the resolvent average to the geometric mean. Some applications to matrix functions are also given
We consider a general class of random matrices whose entries are centred random variables, independe...
In many applications, data measurements are transformed into matrices. To find a trend in repeated m...
In many applications, data measurements are transformed into matrices. To find a trend in repeated m...
We define a new average — termed the resolvent average — for positive semidefinite matrices. For pos...
AbstractWe define a new average – termed the resolvent average – for positive semidefinite matrices....
Monotone operators and firmly nonexpansive mappings are essential to modern optimization and fixed p...
AbstractVarious explicit expansions of the resolvent of a square complex matrix in a neighborhood of...
AbstractA matrix [aij(α)xij] is shown to be positive semidefinite or positive definite if the matrix...
We show that the set of fixed points of the average of two resolvents can be found from the set of f...
We propose a method to find the Lq mean of a set of symmetric positive-definite (SPD) matrices, for ...
AbstractA sharper form of the arithmetic-geometric-mean inequality for a pair of positive definite m...
International audienceEngineering sciences and applications of mathematics show unambiguously that p...
AbstractWe prove a conjecture of Dubey et al. on the change in the resolvent of a nonnegative matrix...
Symmetric positive definite (SPD) matrices have become fundamental computational objects in many area...
International audienceEngineering sciences and applications of mathematics show unambiguously that p...
We consider a general class of random matrices whose entries are centred random variables, independe...
In many applications, data measurements are transformed into matrices. To find a trend in repeated m...
In many applications, data measurements are transformed into matrices. To find a trend in repeated m...
We define a new average — termed the resolvent average — for positive semidefinite matrices. For pos...
AbstractWe define a new average – termed the resolvent average – for positive semidefinite matrices....
Monotone operators and firmly nonexpansive mappings are essential to modern optimization and fixed p...
AbstractVarious explicit expansions of the resolvent of a square complex matrix in a neighborhood of...
AbstractA matrix [aij(α)xij] is shown to be positive semidefinite or positive definite if the matrix...
We show that the set of fixed points of the average of two resolvents can be found from the set of f...
We propose a method to find the Lq mean of a set of symmetric positive-definite (SPD) matrices, for ...
AbstractA sharper form of the arithmetic-geometric-mean inequality for a pair of positive definite m...
International audienceEngineering sciences and applications of mathematics show unambiguously that p...
AbstractWe prove a conjecture of Dubey et al. on the change in the resolvent of a nonnegative matrix...
Symmetric positive definite (SPD) matrices have become fundamental computational objects in many area...
International audienceEngineering sciences and applications of mathematics show unambiguously that p...
We consider a general class of random matrices whose entries are centred random variables, independe...
In many applications, data measurements are transformed into matrices. To find a trend in repeated m...
In many applications, data measurements are transformed into matrices. To find a trend in repeated m...