Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 91-93).Since its development in 1971, the Bathe subspace iteration method has been widely-used to solve the generalized symmetric-definite eigenvalue problem. The method is particularly useful for solving large eigenvalue problems when only a few of the least dominant eigenpairs are sought. In reference [18], an enriched subspace iteration method was proposed that accelerated the convergence of the basic method by replacing some of the iteration vectors with more effective turning vectors. In this thesis, we build upon this recent acceleration effort and further enrich...
The generalized Davidson (GD) method can be viewed as a generalization of the preconditioned steepes...
This paper improves the eigenpair approximations obtained from the automated multilevel substructuri...
AbstractThis paper presents novel perturbation bounds for generalized symmetric positive definite ei...
The subspace iteration method is a very classical method for solving large general eigenvalue proble...
In subspace iteration method (SIM), the relative difference of approximated eigenvalues between two ...
The subspace iteration method is widely used for the computation of a few smallest eigenvalues and t...
Iterative algorithms for large-scale eigenpair computation of symmetric matrices are mostly based on...
AbstractThe pseudo symmetric subspace iteration method is an efficient technique for computing mode ...
We discuss the close connection between eigenvalue computation and optimization using the Newton met...
Subspace Iteration (SI) is perhaps one of the earliest iterative algorithmsused as a numerical eigen...
We discuss a novel approach for the computation of a number of eigenvalues and eigenvectors of the s...
Abstract. The aim of this paper is to provide a convergence analysis for a preconditioned subspace i...
Sequences of eigenvalue problems consistently appear in a large class of applications based on the i...
We present a new subspace iteration method for the efficient computation of several smallest eigenva...
The asymptotic iteration method is a technique for solving analytically and approximately the linear...
The generalized Davidson (GD) method can be viewed as a generalization of the preconditioned steepes...
This paper improves the eigenpair approximations obtained from the automated multilevel substructuri...
AbstractThis paper presents novel perturbation bounds for generalized symmetric positive definite ei...
The subspace iteration method is a very classical method for solving large general eigenvalue proble...
In subspace iteration method (SIM), the relative difference of approximated eigenvalues between two ...
The subspace iteration method is widely used for the computation of a few smallest eigenvalues and t...
Iterative algorithms for large-scale eigenpair computation of symmetric matrices are mostly based on...
AbstractThe pseudo symmetric subspace iteration method is an efficient technique for computing mode ...
We discuss the close connection between eigenvalue computation and optimization using the Newton met...
Subspace Iteration (SI) is perhaps one of the earliest iterative algorithmsused as a numerical eigen...
We discuss a novel approach for the computation of a number of eigenvalues and eigenvectors of the s...
Abstract. The aim of this paper is to provide a convergence analysis for a preconditioned subspace i...
Sequences of eigenvalue problems consistently appear in a large class of applications based on the i...
We present a new subspace iteration method for the efficient computation of several smallest eigenva...
The asymptotic iteration method is a technique for solving analytically and approximately the linear...
The generalized Davidson (GD) method can be viewed as a generalization of the preconditioned steepes...
This paper improves the eigenpair approximations obtained from the automated multilevel substructuri...
AbstractThis paper presents novel perturbation bounds for generalized symmetric positive definite ei...