Abstract
Localization-based sparse direct solvers provide a general framework for preconditioning sparse representations of integral equation formulations of magnetostatic field problems. However, problems involving complex meshes and geometries often lead to poorly conditioned system matrices. In some cases, localization-based preconditioners fail to yield convergent iterative solutions for these matrices. In this presentation it is shown that incorporating a multilevel matrix binormalization significantly increases the effectiveness of localization-based preconditioners.
Original language | English |
---|---|
Title of host publication | 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings |
Pages | 1669-1670 |
Number of pages | 2 |
ISBN (Electronic) | 9781728106922 |
DOIs | |
State | Published - Jul 2019 |
Event | 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Atlanta, United States Duration: Jul 7 2019 → Jul 12 2019 |
Publication series
Name | 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings |
---|
Conference
Conference | 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 |
---|---|
Country/Territory | United States |
City | Atlanta |
Period | 7/7/19 → 7/12/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Funding
This work was supported in part by the Office of Naval Research under Grant N00014-16-1-3066.
Funders | Funder number |
---|---|
Office of Naval Research | N00014-16-1-3066 |
Keywords
- Magnetostatic fields
- Nyström methods
- Sparse solvers
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
- Instrumentation