A Novel Hybrid Algorithm for Source Reconstruction Method in Near-field Prediction

A Novel Hybrid Algorithm for Source Reconstruction Method in Near-field Prediction | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL International Journal of Numerical Modelling: Electronic Networks, Devices and Fields This is a preprint and has not been peer reviewed. Data may be preliminary. 19 January 2025 V1 Latest version Share on A Novel Hybrid Algorithm for Source Reconstruction Method in Near-field Prediction Authors : Chenxi Li , Jian Pang , Qingzhi Wu 0000-0002-3051-2846 [email protected] , and Yuehang Xu 0000-0003-1706-2681 Authors Info & Affiliations https://doi.org/10.22541/au.173731967.78096511/v1 Published International Journal of Numerical Modelling: Electronic Networks, Devices and Fields Version of record Peer review timeline 344 views 245 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Advanced packaging in electronic systems presents new challenges for electromagnetic interference issues. The source reconstruction method (SRM) based on near-field scanning provides a solution for locating electromagnetic interference sources and reconstructing the electromagnetic field inside the package. The traditional SRM based on least squares methods relies on phase information, leading to expensive measurement facilities and complex testing processes. As a result, phaseless SRMs with lower testing requirement have become a research hotspot. However, these methods require solving a nonlinear equation, which lacks an explicit solution and poses difficulties in extracting the equivalent radiation source. To address this issue, a new phaseless SRM that achieves high precision and efficiency is proposed. The method combines the advantages of differential evolution (DE) algorithm with the covariance matrix adaptation evolution strategy (CMA-ES) algorithm, offering fast convergence speed and high accuracy. Compared to conventional DE algorithm, the proposed hybrid method reduces the error of the reconstructed field on an average of 9% and improves the accuracy of the predicted field from 82% to 85% while accelerating convergence. Supplementary Material File (ijnm-script-main.pdf) Download 1.81 MB Information & Authors Information Version history V1 Version 1 19 January 2025 Peer review timeline Published International Journal of Numerical Modelling: Electronic Networks, Devices and Fields Version of Record 3 Mar 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection International Journal of Numerical Modelling: Electronic Networks, Devices and Fields Keywords electromagnetic interference global optimization source reconstruction methods Authors Affiliations Chenxi Li University of Electronic Science and Technology of China School of Electronic Science and Engineering View all articles by this author Jian Pang Shanghai Jiao Tong University View all articles by this author Qingzhi Wu 0000-0002-3051-2846 [email protected] University of Electronic Science and Technology of China School of Electronic Science and Engineering View all articles by this author Yuehang Xu 0000-0003-1706-2681 University of Electronic Science and Technology of China School of Electronic Science and Engineering View all articles by this author Metrics & Citations Metrics Article Usage 344 views 245 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Chenxi Li, Jian Pang, Qingzhi Wu, et al. A Novel Hybrid Algorithm for Source Reconstruction Method in Near-field Prediction. Authorea . 19 January 2025. DOI: https://doi.org/10.22541/au.173731967.78096511/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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