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Conference Paper: Machine learning based method of moments (ML-MoM)

TitleMachine learning based method of moments (ML-MoM)
Authors
Issue Date2017
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000033
Citation
2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, San Diego, CA, USA, 9-14 July 2017, p. 973-974 How to Cite?
AbstractThis paper proposes a novel method by rethinking the method of moments (MoM) solving process into a machine learning training process. Based on the artificial neural network (ANN), the conventional MoM matrix is treated as the training data set, based on which machine learning training process becomes conventional linear algebra MoM solving process. The trained result is the solution of MoM. The multiple linear regression (MLR) is utilized to train the model. Amazon Web Service (AWS) is used as the computations platform to utilize the existing hardware and software resources for machine learning. To verify the feasibility of the proposed new machine learning based method of moments (ML-MoM), we choose the static parasitic capacitance extraction and dynamic electromagnetics scattering as examples. The proposed novel idea opens a new gateway between conventional computational electromagnetics and machine learning algorithms with various application potentials.
Persistent Identifierhttp://hdl.handle.net/10722/259718

 

DC FieldValueLanguage
dc.contributor.authorYao, HM-
dc.contributor.authorJiang, L-
dc.contributor.authorQin, YW-
dc.date.accessioned2018-09-03T04:12:45Z-
dc.date.available2018-09-03T04:12:45Z-
dc.date.issued2017-
dc.identifier.citation2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, San Diego, CA, USA, 9-14 July 2017, p. 973-974-
dc.identifier.urihttp://hdl.handle.net/10722/259718-
dc.description.abstractThis paper proposes a novel method by rethinking the method of moments (MoM) solving process into a machine learning training process. Based on the artificial neural network (ANN), the conventional MoM matrix is treated as the training data set, based on which machine learning training process becomes conventional linear algebra MoM solving process. The trained result is the solution of MoM. The multiple linear regression (MLR) is utilized to train the model. Amazon Web Service (AWS) is used as the computations platform to utilize the existing hardware and software resources for machine learning. To verify the feasibility of the proposed new machine learning based method of moments (ML-MoM), we choose the static parasitic capacitance extraction and dynamic electromagnetics scattering as examples. The proposed novel idea opens a new gateway between conventional computational electromagnetics and machine learning algorithms with various application potentials.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000033-
dc.relation.ispartofIEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting Proceedings-
dc.rightsIEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting Proceedings. Copyright © IEEE.-
dc.rights©2017 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.titleMachine learning based method of moments (ML-MoM)-
dc.typeConference_Paper-
dc.identifier.emailJiang, L: jianglj@hku.hk-
dc.identifier.emailQin, YW: h1181247@connect.hku.hk-
dc.identifier.authorityJiang, L=rp01338-
dc.identifier.doi10.1109/APUSNCURSINRSM.2017.8072529-
dc.identifier.hkuros289472-
dc.identifier.spage973-
dc.identifier.epage974-
dc.publisher.placeUnited States-

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