AbstractEigenvalue computations for structured rank matrices are the subject of many investigations nowadays. There exist methods for transforming matrices into structured rank form, QR-algorithms for semiseparable and semiseparable plus diagonal form, methods for reducing structured rank matrices efficiently to Hessenberg form and so forth.Eigenvalue computations for the symmetric case, involving semiseparable and semiseparable plus diagonal matrices have been thoroughly explored.A first attempt for computing the eigenvalues of nonsymmetric matrices via intermediate Hessenberg-like matrices (i.e. a matrix having all subblocks in the lower triangular part of rank at most one) was restricted to the single shift strategy. Unfortunately this l...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
AbstractIn this paper we design a fast new algorithm for reducing an N×N quasiseparable matrix to up...
Hermitian plus possibly unhermitian low rank matrices can be efficiently reduced into Hessenberg for...
Eigenvalue computations for structured rank matrices are the subject of many investigations nowadays...
Abstract. This paper proposes a new type of iteration for computing eigenvalues of semiseparable (pl...
AbstractIn this paper we describe how to compute the eigenvalues of a unitary rank structured matrix...
AbstractThis manuscript focusses on an alternative method for computing the eigenvalues of a pencil ...
This manuscript focusses on the translation of the traditional eigenvalue problem, based on sparse m...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
In the last few years many numerical techniques for computing eigenvalues of structured rank matrice...
AbstractIn an earlier paper we introduced the classes of polynomial and rank structures, both of the...
AbstractIn this paper, we present a novel method for solving the unitary Hessenberg eigenvalue probl...
Hermitian plus possibly non-Hermitian low rank matrices can be efficiently reduced into Hessenberg f...
Hermitian plus possibly non-Hermitian low rank matrices can be efficiently reduced into Hessenberg f...
In this paper an implicit (double) shifted QR-method for computing the eigenvalues of companion and ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
AbstractIn this paper we design a fast new algorithm for reducing an N×N quasiseparable matrix to up...
Hermitian plus possibly unhermitian low rank matrices can be efficiently reduced into Hessenberg for...
Eigenvalue computations for structured rank matrices are the subject of many investigations nowadays...
Abstract. This paper proposes a new type of iteration for computing eigenvalues of semiseparable (pl...
AbstractIn this paper we describe how to compute the eigenvalues of a unitary rank structured matrix...
AbstractThis manuscript focusses on an alternative method for computing the eigenvalues of a pencil ...
This manuscript focusses on the translation of the traditional eigenvalue problem, based on sparse m...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
In the last few years many numerical techniques for computing eigenvalues of structured rank matrice...
AbstractIn an earlier paper we introduced the classes of polynomial and rank structures, both of the...
AbstractIn this paper, we present a novel method for solving the unitary Hessenberg eigenvalue probl...
Hermitian plus possibly non-Hermitian low rank matrices can be efficiently reduced into Hessenberg f...
Hermitian plus possibly non-Hermitian low rank matrices can be efficiently reduced into Hessenberg f...
In this paper an implicit (double) shifted QR-method for computing the eigenvalues of companion and ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
AbstractIn this paper we design a fast new algorithm for reducing an N×N quasiseparable matrix to up...
Hermitian plus possibly unhermitian low rank matrices can be efficiently reduced into Hessenberg for...