Kirk M. Soodhalter: Krylov subspace methods with fixed memory requirements: Nearly Hermitian linear systems and subspace recycling. Temple University, 2012, (PhD Thesis, Supervisor: Daniel B. Szyld).

Abstract

Krylov subspace iterative methods provide an effective tool for reducing
the solution of large linear systems to a size for which a direct
solver may be applied. However, the problems of limited storage and
speed are still a concern. Therefore, in this dissertation work,
we present iterative Krylov subspace algorithms for non-Hermitian
systems which do have fixed memory requirements and have favorable
convergence characteristics.

Links

    BibTeX (Download)

    @phdthesis{S.2012,
title = {Krylov subspace methods with fixed memory requirements: Nearly Hermitian 
	linear systems and subspace recycling},
author = {Kirk M. Soodhalter},
year  = {2012},
date = {2012-01-01},
urldate = {2012-01-01},
school = {Temple University},
abstract = {Krylov subspace iterative methods provide an effective tool for reducing 
	the solution of large linear systems to a size for which a direct 
	solver may be applied. However, the problems of limited storage and 
	speed are still a concern. Therefore, in this dissertation work, 
	we present iterative Krylov subspace algorithms for non-Hermitian 
	systems which do have fixed memory requirements and have favorable 
	convergence characteristics.},
note = {PhD Thesis, Supervisor: Daniel B. Szyld},
keywords = {thesis},
pubstate = {published},
tppubtype = {phdthesis}
}