AbstractLet A be a square symmetric n × n matrix, φ be a vector from Rn, and f be a function defined on the spectral interval of A. The problem of computation of the vector u = f(A)φ arises very often in mathematical physics.We propose the following method to compute u. First, perform m steps of the Lanczos method with A and φ. Define the spectral Lanczos decomposition method (SLDM) solution as um = ∥ φ ∥Qf(H)e1, where Q is the n × m matrix of the m Lanczos vectors and H is the m × m tridiagonal symmetric matrix of the Lanczos method. We obtain estimates for ∥ u − um ∥ that are stable in the presence of computer round-off errors when using the simple Lanczos method.We concentrate on computation of exp(− tA)φ, when A is nonnegative definite....
This paper investigates the convergence of the Lanczos method for computing the smallest eigenpair o...
In the past the Lanczos algorithm has proven to be a very useful tool in the study of molecular dyna...
AbstractWe prove strictly monotonic error decrease in the Euclidian norm of the Krylov subspace appr...
AbstractLet A be a square symmetric n × n matrix, φ be a vector from Rn, and f be a function defined...
AbstractLet the Cauchy problem for a symmetrical homogeneous ODE system be solved by a difference sc...
A new stable and efficient implementation of the Lanczos algorithm is presented. The algorithm is a ...
Includes bibliographical references (p. 70-74)We are interested in computing eigenvalues and eigenve...
We analyze the Lanczos method for matrix function approximation (Lanczos-FA), an iterative algorithm...
AbstractThe Lanczos algorithm for tridiagonalizing a given matrix A generates a sequence of approxim...
AbstractFirst we identify five options which can be used to distinguish one Lanczos eigenelement pro...
In this paper, we investigate a method for restarting the Lanczos method for approximating the matri...
In this paper, we investigate a method for restarting the Lanczos method for approximating the matri...
Masters thesisIn this thesis we examine the connections between orthogonal polynomials and the Lanc...
AbstractEigenvalues and eigenvectors of a large sparse symmetric matrix A can be found accurately an...
Lanczos method for solving a system of linear equations can be derived by using formal orthogonal po...
This paper investigates the convergence of the Lanczos method for computing the smallest eigenpair o...
In the past the Lanczos algorithm has proven to be a very useful tool in the study of molecular dyna...
AbstractWe prove strictly monotonic error decrease in the Euclidian norm of the Krylov subspace appr...
AbstractLet A be a square symmetric n × n matrix, φ be a vector from Rn, and f be a function defined...
AbstractLet the Cauchy problem for a symmetrical homogeneous ODE system be solved by a difference sc...
A new stable and efficient implementation of the Lanczos algorithm is presented. The algorithm is a ...
Includes bibliographical references (p. 70-74)We are interested in computing eigenvalues and eigenve...
We analyze the Lanczos method for matrix function approximation (Lanczos-FA), an iterative algorithm...
AbstractThe Lanczos algorithm for tridiagonalizing a given matrix A generates a sequence of approxim...
AbstractFirst we identify five options which can be used to distinguish one Lanczos eigenelement pro...
In this paper, we investigate a method for restarting the Lanczos method for approximating the matri...
In this paper, we investigate a method for restarting the Lanczos method for approximating the matri...
Masters thesisIn this thesis we examine the connections between orthogonal polynomials and the Lanc...
AbstractEigenvalues and eigenvectors of a large sparse symmetric matrix A can be found accurately an...
Lanczos method for solving a system of linear equations can be derived by using formal orthogonal po...
This paper investigates the convergence of the Lanczos method for computing the smallest eigenpair o...
In the past the Lanczos algorithm has proven to be a very useful tool in the study of molecular dyna...
AbstractWe prove strictly monotonic error decrease in the Euclidian norm of the Krylov subspace appr...