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Conference Paper: Blackbox macro-modeling of the nonlinearity based on Volterra series representation of X-parameters

TitleBlackbox macro-modeling of the nonlinearity based on Volterra series representation of X-parameters
Authors
KeywordsVolterra series
X-parameters
Macro-modeling
Issue Date2014
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000236
Citation
The 23rd IEEE Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS 2014), Portland, OR., 26-29 October 2014. In Conference Proceedings, 2014, p. 85-88 How to Cite?
AbstractVolterra series representation is a powerful mathematical model for nonlinear devices. However, the difficulties in determining higher-order Volterra kernels limited its broader applications. This paper proposed a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters for the first time. Then the Vandermonde method is employed to separate different orders of Volterra kernels at the same frequency, which leads to a highly efficient extraction process. The proposed Volterra series representation based on X-parameters is further benchmarked for verification. The proposed new algorithm is very useful for the blackbox macro-modeling of nonlinear devices and systems. © 2014 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/216378
ISBN

 

DC FieldValueLanguage
dc.contributor.authorXiong, XY-
dc.contributor.authorJiang, L-
dc.contributor.authorShutt-Aine, JE-
dc.contributor.authorChew, WC-
dc.date.accessioned2015-09-18T05:25:44Z-
dc.date.available2015-09-18T05:25:44Z-
dc.date.issued2014-
dc.identifier.citationThe 23rd IEEE Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS 2014), Portland, OR., 26-29 October 2014. In Conference Proceedings, 2014, p. 85-88-
dc.identifier.isbn978-1-4799-3643-4-
dc.identifier.urihttp://hdl.handle.net/10722/216378-
dc.description.abstractVolterra series representation is a powerful mathematical model for nonlinear devices. However, the difficulties in determining higher-order Volterra kernels limited its broader applications. This paper proposed a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters for the first time. Then the Vandermonde method is employed to separate different orders of Volterra kernels at the same frequency, which leads to a highly efficient extraction process. The proposed Volterra series representation based on X-parameters is further benchmarked for verification. The proposed new algorithm is very useful for the blackbox macro-modeling of nonlinear devices and systems. © 2014 IEEE.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000236-
dc.relation.ispartofIEEE Topical Meeting on Electrical Performance of Electronic Packaging and Systems (EPEPS)-
dc.rightsIEEE Topical Meeting on Electrical Performance of Electronic Packaging and Systems (EPEPS). Copyright © IEEE.-
dc.rights©2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectVolterra series-
dc.subjectX-parameters-
dc.subjectMacro-modeling-
dc.titleBlackbox macro-modeling of the nonlinearity based on Volterra series representation of X-parameters-
dc.typeConference_Paper-
dc.identifier.emailXiong, XY: xyxiong@hku.hk-
dc.identifier.emailJiang, L: jianglj@hku.hk-
dc.identifier.emailChew, WC: wcchew@hkucc.hku.hk-
dc.identifier.authorityJiang, L=rp01338-
dc.identifier.authorityChew, WC=rp00656-
dc.description.naturepostprint-
dc.identifier.doi10.1109/EPEPS.2014.7103601-
dc.identifier.scopuseid_2-s2.0-84937124624-
dc.identifier.hkuros252053-
dc.identifier.spage85-
dc.identifier.epage88-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151103-

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