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University of Illinois at Urbana-Champaign
On Solving the Large Sparse Generalized Eigenvalue Problem
Abstract
dc:descriptionThis thesis presents an algorithm for solving the large sparse generalized eigenvalue problem Ax = (lamda)Bx. The matrices A and B are assumed to be symmetric, and haphazardly sparse, with B being positive definite. The problem is treated from a constrained optimization approach and an inverse iteration is developed which requires the solution of linear algebraic systems only to the accuracy demanded by a given subspace. The convergence of the method is discussed, and the rate of convergence is improved by using shifting with the Ritz approximations. Numerical results are presented, and aspects concerning an implementation on a parallel computer are discussed.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2014
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Wisniewski, John Aruthur
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (UMI)AAI8114504
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/66452