Adaptive generation of excitation-independent characteristic basis functions

Chen, X; Gu, C; Mittra, R

Adaptive generation of excitation-independent characteristic basis functions

Chen, X Gu, C Mittra, R

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Publication Type:: Conference Proceeding
Citation:: 2017 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2017, 2017, pp. 29 - 30
Issue Date:: 2017-10-18

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Field	Value	Language
dc.contributor.author	Chen, X	en_US
dc.contributor.author	Gu, C	en_US
dc.contributor.author	Mittra, R https://orcid.org/0000-0002-0960-2708	en_US
dc.date.issued	2017-10-18	en_US
dc.identifier.citation	2017 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2017, 2017, pp. 29 - 30	en_US
dc.identifier.isbn	9781509044122	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126505
dc.description.abstract	© 2017 IEEE. The Characteristic Basis Function Method (CBFM) has been widely used in recent years to solve a variety of electromagnetic scattering problems because it offers a way to direct-solve large problems without the use of iteration, enabling it to not only handle multiple excitation (r.h.s.) problems in an efficient manner, but to also bypass the issues of ill-conditioning as well as generation of preconditioners. In the past, the choice of number of plane wave excitations used to generate the excitation-independent CBFs have been made empirically, on an ad hoc basis, rather than systematically. This paper presents an adaptive approach for generating the CBFs, which provides a systematic way to determine of the number of plane waves needed for CBF generation, and this in turn renders the CBFM computationally efficient.	en_US
dc.relation.ispartof	2017 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2017	en_US
dc.relation.isbasedon	10.1109/USNC-URSI.2017.8074881	en_US
dc.title	Adaptive generation of excitation-independent characteristic basis functions	en_US
dc.type	Conference Proceeding
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. The Characteristic Basis Function Method (CBFM) has been widely used in recent years to solve a variety of electromagnetic scattering problems because it offers a way to direct-solve large problems without the use of iteration, enabling it to not only handle multiple excitation (r.h.s.) problems in an efficient manner, but to also bypass the issues of ill-conditioning as well as generation of preconditioners. In the past, the choice of number of plane wave excitations used to generate the excitation-independent CBFs have been made empirically, on an ad hoc basis, rather than systematically. This paper presents an adaptive approach for generating the CBFs, which provides a systematic way to determine of the number of plane waves needed for CBF generation, and this in turn renders the CBFM computationally efficient.

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http://hdl.handle.net/10453/126505