The implicit Q theorem for Hessenberg matrices is a widespread and powerful theorem. It is used in the development of, for example, implicit QR algorithms to compute the eigendecomposition of Hessenberg matrices. Moreover it can also be used to prove the essential uniqueness of orthogonal similarity transformations of matrices to Hessenberg form. The theorem is also valid for symmetric tridiagonal matrices, proving thereby also in the symmetric case its power.status: publishe
AbstractLet H be an n × n unitary right Hessenberg matrix with positive subdiagonal elements. Using ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
AbstractIn this paper, we present a novel method for solving the unitary Hessenberg eigenvalue probl...
The implicit Q-theorem for Hessenberg matrices is a widespread and powerful theorem. It is used in ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
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...
Hermitian plus possibly unhermitian low rank matrices can be efficiently reduced into Hessenberg for...
Hermitian plus possibly non-Hermitian low rank matrices can be efficiently reduced into Hessenberg f...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...
In this paper an implicit (double) shifted QR-method for computing the eigenvalues of companion and ...
A unitary symplectic similarity transformation for certain Hamiltonian matrices to extended Hamilton...
AbstractIn this paper we describe how to compute the eigenvalues of a unitary rank structured matrix...
Recently an extension of the class of matrices admitting a Francis type of multishift QR algorithm w...
AbstractThere are few normal Hessenberg matrices. The connection with moment matrices sheds light on...
AbstractLet H be an n × n unitary right Hessenberg matrix with positive subdiagonal elements. Using ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
AbstractIn this paper, we present a novel method for solving the unitary Hessenberg eigenvalue probl...
The implicit Q-theorem for Hessenberg matrices is a widespread and powerful theorem. It is used in ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
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...
Hermitian plus possibly unhermitian low rank matrices can be efficiently reduced into Hessenberg for...
Hermitian plus possibly non-Hermitian low rank matrices can be efficiently reduced into Hessenberg f...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If i...
In this paper an implicit (double) shifted QR-method for computing the eigenvalues of companion and ...
A unitary symplectic similarity transformation for certain Hamiltonian matrices to extended Hamilton...
AbstractIn this paper we describe how to compute the eigenvalues of a unitary rank structured matrix...
Recently an extension of the class of matrices admitting a Francis type of multishift QR algorithm w...
AbstractThere are few normal Hessenberg matrices. The connection with moment matrices sheds light on...
AbstractLet H be an n × n unitary right Hessenberg matrix with positive subdiagonal elements. Using ...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
AbstractIn this paper, we present a novel method for solving the unitary Hessenberg eigenvalue probl...