This manuscript focusses on an alternative method for computing the eigenvalues of a pencil of two matrices, based on semiseparable matrices. An effective reduction of a matrix pair to lower semiseparable, upper triangular form will be presented as well as a QZ-iteration for this matrix pair. Important to remark is that this reduction procedure also inherits a kind of nested subspace iteration as was the case when solving the standard eigenvalue problem with semiseparable matrices. It will also be shown, that the QZ-iteration for a semiseparable-triangular matrix pair is closely related to the QZ-iteration for a Hessenberg-triangular matrix pair.status: publishe
International audienceWe design a fast implicit real QZ algorithm for eigenvalue computation of stru...
We design a fast implicit real QZ algorithm for eigenvalue computation of structured companion penci...
The matrix eigenvalue problem is often encountered in scientific computing applications. Although it...
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...
Recently an extension of the class of matrices admitting a Francis type of multishift QR algorithm w...
Abstract. This paper proposes a new type of iteration for computing eigenvalues of semiseparable (pl...
The Jacobi-Davidson subspace iteration method oers possibilities for solving a variety of eigenprobl...
We propose a rational QZ method for the solution of the dense, unsymmetric generalized eigenvalue pr...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
This algorithm is an extension of Moler and Stewart's QZ algorithm with some added features for savi...
AbstractA new algorithm for the computation of eigenvalues of a nonsymmetric matrix pencil is descri...
Eigenvalue computations for structured rank matrices are the subject of many investigations nowadays...
In the article "A Rational QZ Method"" by D. Camps, K. Meerbergen, and R. Vandebril [SIAM J. Matrix ...
An algorithm to reduce a symmetric matrix to a similar semiseparable one of semiseparability rank 1,...
International audienceWe design a fast implicit real QZ algorithm for eigenvalue computation of stru...
We design a fast implicit real QZ algorithm for eigenvalue computation of structured companion penci...
The matrix eigenvalue problem is often encountered in scientific computing applications. Although it...
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...
Recently an extension of the class of matrices admitting a Francis type of multishift QR algorithm w...
Abstract. This paper proposes a new type of iteration for computing eigenvalues of semiseparable (pl...
The Jacobi-Davidson subspace iteration method oers possibilities for solving a variety of eigenprobl...
We propose a rational QZ method for the solution of the dense, unsymmetric generalized eigenvalue pr...
The QR algorithm is one of the classical methods to compute the eigendecomposition of a matrix. If ...
This algorithm is an extension of Moler and Stewart's QZ algorithm with some added features for savi...
AbstractA new algorithm for the computation of eigenvalues of a nonsymmetric matrix pencil is descri...
Eigenvalue computations for structured rank matrices are the subject of many investigations nowadays...
In the article "A Rational QZ Method"" by D. Camps, K. Meerbergen, and R. Vandebril [SIAM J. Matrix ...
An algorithm to reduce a symmetric matrix to a similar semiseparable one of semiseparability rank 1,...
International audienceWe design a fast implicit real QZ algorithm for eigenvalue computation of stru...
We design a fast implicit real QZ algorithm for eigenvalue computation of structured companion penci...
The matrix eigenvalue problem is often encountered in scientific computing applications. Although it...