Implications of recompression for grid-based low-rank approximation techniques

Jon T. Kelley, Tian Yao, Yaniv Brick, Ali E. Yilmaz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Low-rank compression of moment matrix blocks, representing interactions between clusters of vector basis/testing functions, is often done by a rank-revealing analysis of a simplified grid-to-grid interaction matrix, followed by inter/anterpolation and recompression. While this can provide a close estimate of the rank, it can lead to large errors in the compressed representation due to misrepresentation by grids of the underlying relative orientations of the vector functions. The potential hazard is demonstrated via a simplified example for the dyadic formulation.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages789-790
Number of pages2
ISBN (Electronic)9781728106922
DOIs
StatePublished - 1 Jul 2019
Event2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Atlanta, United States
Duration: 7 Jul 201912 Jul 2019

Publication series

Name2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings

Conference

Conference2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019
Country/TerritoryUnited States
CityAtlanta
Period7/07/1912/07/19

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