New Schemes for Solving the Principal Eigenvalue Problems of Perron-like Matrices via Polynomial Approximations of Matrix Exponentials

08/16/2020
by   Desheng Li, et al.
0

A real square matrix is Perron-like if it has a real eigenvalue s, called the principal eigenvalue of the matrix, and μ<s for any other eigenvalue μ. Nonnegative matrices and symmetric ones are typical examples of this class of matrices. The main purpose of this paper is to develop a set of new schemes to compute the principal eigenvalues of Perron-like matrices and the associated generalized eigenspaces by using polynomial approximations of matrix exponentials. Numerical examples show that these schemes are effective in practice.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/24/2021

A global quadratic speed-up for computing the principal eigenvalue of Perron-like operators

We consider a new algorithm in light of the min-max Collatz-Wielandt for...
research
05/30/2021

An iterative Jacobi-like algorithm to compute a few sparse eigenvalue-eigenvector pairs

In this paper, we describe a new algorithm to compute the extreme eigenv...
research
01/19/2020

How to Detect and Construct N-matrices

N-matrices are real n× n matrices all of whose principal minors are nega...
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
01/16/2023

Computing the closest singular matrix polynomial

Given a matrix polynomial P ( λ)= A_0 + λ A_1 + … + λ^d A_d, with A_0,…,...
research
05/11/2020

Well-conditioned eigenvalue problems that overflow

In this note we present a parameterized class of lower triangular matric...
research
02/17/2022

A note on switching eigenvalues under small perturbations

Sensitivity of eigenvectors and eigenvalues of symmetric matrix estimate...

Please sign up or login with your details

Forgot password? Click here to reset