AbstractThis paper presents an implementation on Graphics Processing Units of QR-Householder algorithm used to find all the eigenvalues and eigenvectors of many small hermitian matrices (double precision) in a very short time to address time constraints for Radar issues
This paper explores the early implementation of high-performance routines for the solution of multip...
Many fields make use of the concepts about eigenvalues in their studies. In engineering, physics, st...
We show how both the tridiagonal and bidiagonal QR algorithms can be restructured so that they be- ...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
This project deals with computation of eigenvalues and eigenvectors of Hermitian positive-semidefini...
The QR-algorithm is a popular numerical method for the computation of eigenvalues of matrices. All e...
International audienceWe consider the problem of implementing an algorithm for the extraction of lea...
AbstractThe QR-algorithm is a popular numerical method for the computation of eigenvalues of matrice...
As a recurrent problem in numerical analysis and computational science, eigenvector and eigenvalue d...
In this paper a parallel implementation of the QR algorithm for the eigenvalues of a non-Hermitian m...
The class of eigenvalue problems for upper Hessenberg matrices of banded-plus-spike form includes co...
The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrice...
This paper explores the early implementation of high-performance routines for the solution of multip...
This report demonstrates parallel versions of the Eispack functions TRED2 and TQL2 for finding all...
This paper explores the early implementation of high- performance routines for the solution of multi...
This paper explores the early implementation of high-performance routines for the solution of multip...
Many fields make use of the concepts about eigenvalues in their studies. In engineering, physics, st...
We show how both the tridiagonal and bidiagonal QR algorithms can be restructured so that they be- ...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
This project deals with computation of eigenvalues and eigenvectors of Hermitian positive-semidefini...
The QR-algorithm is a popular numerical method for the computation of eigenvalues of matrices. All e...
International audienceWe consider the problem of implementing an algorithm for the extraction of lea...
AbstractThe QR-algorithm is a popular numerical method for the computation of eigenvalues of matrice...
As a recurrent problem in numerical analysis and computational science, eigenvector and eigenvalue d...
In this paper a parallel implementation of the QR algorithm for the eigenvalues of a non-Hermitian m...
The class of eigenvalue problems for upper Hessenberg matrices of banded-plus-spike form includes co...
The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrice...
This paper explores the early implementation of high-performance routines for the solution of multip...
This report demonstrates parallel versions of the Eispack functions TRED2 and TQL2 for finding all...
This paper explores the early implementation of high- performance routines for the solution of multi...
This paper explores the early implementation of high-performance routines for the solution of multip...
Many fields make use of the concepts about eigenvalues in their studies. In engineering, physics, st...
We show how both the tridiagonal and bidiagonal QR algorithms can be restructured so that they be- ...
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