AbstractThe computation of eigenvalues and eigenvectors of a real symmetric matrix A with distinct eigenvalues can be speeded up at the end of the Jacobi process when the off-diagonal elements have become sufficiently small for A to be regarded as a perturbation of a diagonal matrix. A leading-order approximation to the eigensolution is calculated by formulae particularly suitable for the distributed array processor (DAP). A single application of this direct method reduces A to diagonal form and is asymptotically equivalent to an entire sweep of the Jacobi method
AbstractSolving dense symmetric eigenvalue problems and computing singular value decompositions cont...
AbstractThis paper deals with the eigenproblem of positive definite matrices. A numerical algorithm,...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...
AbstractThe computation of eigenvalues and eigenvectors of a real symmetric matrix A with distinct e...
AbstractThis paper discusses a generalization for non-Hermitian matrices of the Jacobi eigenvalue pr...
The paper proposes a parallel algorithm to compute the eigenvalues and eigenvectors of a real symmet...
Parallel Jacobi-like algorithms are presented for computing a singular-value decomposition of an $m...
AbstractThis article presents a new Jacobi-like eigenvalue algorithm for non-Hermitian almost diagon...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...
An algorithm is presented for computing the eigenvalues and eigenvectors of an n x n real symmetric...
A new parallel Jacobi-like algorithm is developed for computing the eigenvalues of a general complex...
A completely parallel algorithm for the symmetric eigenproblem AX = Lambda BX is outlined. The algor...
AbstractWe give a cubic correction step for improving the current eigenvalue algorithms for computin...
An algorithm to solve the eigenproblem for non-symmetric matrices on an $N \times N$ array of mesh ...
The paper describes several efficient parallel implementations of the one-sided hyperbolic Jacobi-ty...
AbstractSolving dense symmetric eigenvalue problems and computing singular value decompositions cont...
AbstractThis paper deals with the eigenproblem of positive definite matrices. A numerical algorithm,...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...
AbstractThe computation of eigenvalues and eigenvectors of a real symmetric matrix A with distinct e...
AbstractThis paper discusses a generalization for non-Hermitian matrices of the Jacobi eigenvalue pr...
The paper proposes a parallel algorithm to compute the eigenvalues and eigenvectors of a real symmet...
Parallel Jacobi-like algorithms are presented for computing a singular-value decomposition of an $m...
AbstractThis article presents a new Jacobi-like eigenvalue algorithm for non-Hermitian almost diagon...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...
An algorithm is presented for computing the eigenvalues and eigenvectors of an n x n real symmetric...
A new parallel Jacobi-like algorithm is developed for computing the eigenvalues of a general complex...
A completely parallel algorithm for the symmetric eigenproblem AX = Lambda BX is outlined. The algor...
AbstractWe give a cubic correction step for improving the current eigenvalue algorithms for computin...
An algorithm to solve the eigenproblem for non-symmetric matrices on an $N \times N$ array of mesh ...
The paper describes several efficient parallel implementations of the one-sided hyperbolic Jacobi-ty...
AbstractSolving dense symmetric eigenvalue problems and computing singular value decompositions cont...
AbstractThis paper deals with the eigenproblem of positive definite matrices. A numerical algorithm,...
AbstractSystolic arrays have become established in principle, if not yet in practice, as a way of in...