On a numerical construction of doubly stochastic matrices with prescribed eigenvalues

08/24/2022
by   Kassem Rammal, et al.
0

We study the inverse eigenvalue problem for finding doubly stochastic matrices with specified eigenvalues. By making use of a combination of Dykstra's algorithm and an alternating projection process onto a non-convex set, we derive hybrid algorithms for finding doubly stochastic matrices and symmetric doubly stochastic matrices with prescribed eigenvalues. Furthermore, we prove that the proposed algorithms converge and linear convergence is also proved. Numerical examples are presented to demonstrate the efficiency of our method.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/20/2018

On constructing orthogonal generalized doubly stochastic matrices

A real quadratic matrix is generalized doubly stochastic (g.d.s.) if all...
research
04/15/2020

A New Constrained Optimization Model for Solving the Nonsymmetric Stochastic Inverse Eigenvalue Problem

The stochastic inverse eigenvalue problem aims to reconstruct a stochast...
research
06/29/2020

A Multilevel Spectral Indicator Method for Eigenvalues of Large Non-Hermitian Matrices

Recently a novel family of eigensolvers, called spectral indicator metho...
research
07/26/2023

Finding roots of complex analytic functions via generalized colleague matrices

We present a scheme for finding all roots of an analytic function in a s...
research
03/13/2023

Distance Evaluation to the Set of Defective Matrices

We treat the problem of the Frobenius distance evaluation from a given m...
research
01/27/2022

Eigenvalues of Autoencoders in Training and at Initialization

In this paper, we investigate the evolution of autoencoders near their i...
research
03/31/2022

A visualisation for conveying the dynamics of iterative eigenvalue algorithms over PSD matrices

We propose a new way of visualising the dynamics of iterative eigenvalue...

Please sign up or login with your details

Forgot password? Click here to reset