We start by introducing a new class of structured matrix polynomials, namely, the class of M-A-structured matrix polynomials, to provide a common framework for many classes of structured matrix polynomials that are important in applications: the classes of (skew-)symmetric, (anti-) palindromic, and alternating matrix polynomials. Then, we introduce the families of M-A-structured strong block minimal bases pencils and of M-A-structured block Kronecker pencils, which are particular examples of block minimal bases pencils recently introduced by Dopico, Lawrence, Perez and Van Dooren, and show that any M-A-structured odd-degree matrix polynomial can be strongly linearized via an M-A-structured block Kronecker pencil. Finally, for the classes of...
AbstractWe derive explicit computable expressions of structured backward errors of approximate eigen...
In this paper we study the backward stability of running a backward stable eigenstructure solver on ...
AbstractThis work is concerned with eigenvalue problems for structured matrix polynomials, including...
We start by introducing a new class of structured matrix polynomials, namely, the class of M-A-struc...
Abstract. We start by introducing a new class of structured matrix polynomials, namely, the class of...
Abstract. We start by introducing a new class of structured matrix polynomials, namely, the class of...
We introduce a new family of strong linearizations of matrix polynomials---which we call "block Kron...
We introduce a new family of strong linearizations of matrix polynomialswhich we call block Kronecke...
We introduce a new family of strong linearizations of matrix polynomials---which we call "block Kron...
We introduce a new family of strong linearizations of matrix polynomialswhich we call block Kronecke...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
One of the most frequently used techniques to solve polynomial eigenvalue problems is linearization,...
We perform a structured backward error analysis of polynomial eigenvalue problems solved via lineari...
AbstractWe derive explicit computable expressions of structured backward errors of approximate eigen...
In this paper we study the backward stability of running a backward stable eigenstructure solver on ...
AbstractThis work is concerned with eigenvalue problems for structured matrix polynomials, including...
We start by introducing a new class of structured matrix polynomials, namely, the class of M-A-struc...
Abstract. We start by introducing a new class of structured matrix polynomials, namely, the class of...
Abstract. We start by introducing a new class of structured matrix polynomials, namely, the class of...
We introduce a new family of strong linearizations of matrix polynomials---which we call "block Kron...
We introduce a new family of strong linearizations of matrix polynomialswhich we call block Kronecke...
We introduce a new family of strong linearizations of matrix polynomials---which we call "block Kron...
We introduce a new family of strong linearizations of matrix polynomialswhich we call block Kronecke...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
One of the most frequently used techniques to solve polynomial eigenvalue problems is linearization,...
We perform a structured backward error analysis of polynomial eigenvalue problems solved via lineari...
AbstractWe derive explicit computable expressions of structured backward errors of approximate eigen...
In this paper we study the backward stability of running a backward stable eigenstructure solver on ...
AbstractThis work is concerned with eigenvalue problems for structured matrix polynomials, including...