The Sherman Morrison Iteration

The Sherman Morrison iteration method is developed to solve regularized least squares problems. Notions of pivoting and splitting are deliberated on to make the method more robust. The Sherman Morrison iteration method is shown to be effective when dealing with an extremely underdetermined least squares problem. The performance of the Sherman Morrison iteration is compared to classic direct methods, as well as iterative methods, in a number of experiments. Specific Matlab implementation of the Sherman Morrison iteration is discussed, with Matlab codes for the method available in the appendix.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Mathematics

Department dc:contributor.department

Mathematics

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2015

Author dc:creator

• Slagel, Joseph Tanner

Chair dc:contributor.committeechair

• Chung, Matthias

Committee members dc:contributor.committeemember

• Gugercin, Serkan
• Chung, Julianne

• Sherman Morrison
• regularized least squares problem
• extremely underdetermined linear system

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:5745

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/52966