AbstractWe show that for the non-Hermitian eigenvalue problem simplified Jacobi–Davidson with preconditioned iterative solves is equivalent to inexact Rayleigh quotient iteration where the preconditioner is altered by a simple rank one change. This extends existing equivalence results to the case of preconditioned iterative solves. Numerical experiments are shown to agree with the theory
Gradient-type iterative methods for solving Hermitian eigenvalue problems can be accelerated by usin...
AbstractIn this paper we analyse inexact inverse iteration for the real symmetric eigenvalue problem...
In the Davidson method, any preconditioner can be exploited for the iterative computation of eigenpa...
AbstractWe show that for the non-Hermitian eigenvalue problem simplified Jacobi–Davidson with precon...
Rayleigh Quotient iteration is an iterative method with some attractive convergence properties for n...
AbstractWe study inexact subspace iteration for solving generalized non-Hermitian eigenvalue problem...
Many methods for computing eigenvalues of a large sparse matrix involve shift-invert transformations...
Rayleigh Quotient iteration is an iterative method with some attractive convergence properties for n...
AbstractThe discretization of eigenvalue problems for partial differential operators is a major sour...
We present a detailed convergence analysis of preconditioned MINRES for approximately solving the l...
Abstract. Rayleigh Quotient iteration is an iterative method with some attractive convergence proper...
AbstractWe incorporate our recent preconditioning techniques into the classical inverse power (Rayle...
AbstractThis paper deals with the convergence analysis of various preconditioned iterations to compu...
AbstractWe discuss two variants of a two-sided Jacobi–Davidson (JD) method, which have asymptoticall...
In the Davidson method, any preconditioner can be exploited for the iterative computation of eigen-p...
Gradient-type iterative methods for solving Hermitian eigenvalue problems can be accelerated by usin...
AbstractIn this paper we analyse inexact inverse iteration for the real symmetric eigenvalue problem...
In the Davidson method, any preconditioner can be exploited for the iterative computation of eigenpa...
AbstractWe show that for the non-Hermitian eigenvalue problem simplified Jacobi–Davidson with precon...
Rayleigh Quotient iteration is an iterative method with some attractive convergence properties for n...
AbstractWe study inexact subspace iteration for solving generalized non-Hermitian eigenvalue problem...
Many methods for computing eigenvalues of a large sparse matrix involve shift-invert transformations...
Rayleigh Quotient iteration is an iterative method with some attractive convergence properties for n...
AbstractThe discretization of eigenvalue problems for partial differential operators is a major sour...
We present a detailed convergence analysis of preconditioned MINRES for approximately solving the l...
Abstract. Rayleigh Quotient iteration is an iterative method with some attractive convergence proper...
AbstractWe incorporate our recent preconditioning techniques into the classical inverse power (Rayle...
AbstractThis paper deals with the convergence analysis of various preconditioned iterations to compu...
AbstractWe discuss two variants of a two-sided Jacobi–Davidson (JD) method, which have asymptoticall...
In the Davidson method, any preconditioner can be exploited for the iterative computation of eigen-p...
Gradient-type iterative methods for solving Hermitian eigenvalue problems can be accelerated by usin...
AbstractIn this paper we analyse inexact inverse iteration for the real symmetric eigenvalue problem...
In the Davidson method, any preconditioner can be exploited for the iterative computation of eigenpa...