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Conference Paper: Machine learning based MoM (ML-MoM) for parasitic capacitance extractions

TitleMachine learning based MoM (ML-MoM) for parasitic capacitance extractions
Authors
Yao, HQin, YWJiang, L
KeywordsArtificial Neural Network
Capacitance Extraction
Machine Learning
Method of Moments
Issue Date2016
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1002555
Citation
Proceedings of 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), Honolulu, HI, USA, 14-16 December 2016, p. 171-173 How to Cite?
DOI: http://dx.doi.org/10.1109/EDAPS.2016.7893155
Persistent Identifierhttp://hdl.handle.net/10722/247806

 

DC FieldValueLanguage
dc.contributor.authorYao, H-
dc.contributor.authorQin, YW-
dc.contributor.authorJiang, L-
dc.date.accessioned2017-10-18T08:32:57Z-
dc.date.available2017-10-18T08:32:57Z-
dc.date.issued2016-
dc.identifier.citationProceedings of 2016 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), Honolulu, HI, USA, 14-16 December 2016, p. 171-173-
dc.identifier.urihttp://hdl.handle.net/10722/247806-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1002555-
dc.relation.ispartofElectrical Design of Advanced Packaging and Systems Symposium Proceedings-
dc.rightsElectrical Design of Advanced Packaging and Systems Symposium Proceedings. Copyright © IEEE.-
dc.rights©2016 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.subjectArtificial Neural Network-
dc.subjectCapacitance Extraction-
dc.subjectMachine Learning-
dc.subjectMethod of Moments-
dc.titleMachine learning based MoM (ML-MoM) for parasitic capacitance extractions-
dc.typeConference_Paper-
dc.identifier.emailJiang, L: jianglj@hku.hk-
dc.identifier.authorityJiang, L=rp01338-
dc.identifier.doi10.1109/EDAPS.2016.7893155-
dc.identifier.scopuseid_2-s2.0-85018398297-
dc.identifier.hkuros280716-
dc.identifier.spage171-
dc.identifier.epage173-
dc.publisher.placeUnited States-

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