AbstractThe nearest symmetric positive semidefinite matrix in the Frobenius norm to an arbitrary real matrix A is shown to be (B + H)/2, where H is the symmetric polar factor of B=(A + AT)/2. In the 2-norm a nearest symmetric positive semidefinite matrix, and its distance δ2(A) from A, are given by a computationally challenging formula due to Halmos. We show how the bisection method can be applied to this formula to compute upper and lower bounds for δ2(A) differing by no more than a given amount. A key ingredient is a stable and efficient test for positive definiteness, based on an attempted Choleski decomposition. For accurate computation of δ2(A) we formulate the problem as one of zero finding and apply a hybrid Newton-bisection algorith...
Indefinite estimates of positive semidefinite matrices arise in many data analysis applications invo...
We describe a bisection method to determine the 2-norm and Frobenius norm - g distance from a given ...
Indefinite estimates of positive semidefinite matrices arise in many data analysis applications invo...
The nearest symmetric positive semidefinite matrix in the Frobenius norm to an arbitrary real matrix...
AbstractThe nearest symmetric positive semidefinite matrix in the Frobenius norm to an arbitrary rea...
This thesis presents new theoretical results and algorithms for two matrix problems with positive se...
AbstractThough the real symmetric positive semidefinite (PSD) matrices and the Euclidean distance ma...
In this paper, we consider the non-symmetric positive semidefinite Procrustes (NSPSDP) problem: Give...
AbstractThe positive semidefinite and Euclidean distance matrix completion problems have received a ...
We consider the theoretical and the computational aspects of some nearness problems in numerical lin...
For arbitrary real matrices F and G, the positive semi-definite Procrustes problem is minimization o...
We describe an important class of semidefinite programming problems that has received scant attentio...
Given a symmetric matrix what is the nearest correlation matrix, that is, the nearest symmetric posi...
AbstractThough the real symmetric positive semidefinite (PSD) matrices and the Euclidean distance ma...
AbstractWe present a semidefinite programming approach for computing optimally conditioned positive ...
Indefinite estimates of positive semidefinite matrices arise in many data analysis applications invo...
We describe a bisection method to determine the 2-norm and Frobenius norm - g distance from a given ...
Indefinite estimates of positive semidefinite matrices arise in many data analysis applications invo...
The nearest symmetric positive semidefinite matrix in the Frobenius norm to an arbitrary real matrix...
AbstractThe nearest symmetric positive semidefinite matrix in the Frobenius norm to an arbitrary rea...
This thesis presents new theoretical results and algorithms for two matrix problems with positive se...
AbstractThough the real symmetric positive semidefinite (PSD) matrices and the Euclidean distance ma...
In this paper, we consider the non-symmetric positive semidefinite Procrustes (NSPSDP) problem: Give...
AbstractThe positive semidefinite and Euclidean distance matrix completion problems have received a ...
We consider the theoretical and the computational aspects of some nearness problems in numerical lin...
For arbitrary real matrices F and G, the positive semi-definite Procrustes problem is minimization o...
We describe an important class of semidefinite programming problems that has received scant attentio...
Given a symmetric matrix what is the nearest correlation matrix, that is, the nearest symmetric posi...
AbstractThough the real symmetric positive semidefinite (PSD) matrices and the Euclidean distance ma...
AbstractWe present a semidefinite programming approach for computing optimally conditioned positive ...
Indefinite estimates of positive semidefinite matrices arise in many data analysis applications invo...
We describe a bisection method to determine the 2-norm and Frobenius norm - g distance from a given ...
Indefinite estimates of positive semidefinite matrices arise in many data analysis applications invo...