Order Reduction Using Laguerre-FDTD with Embedded Neural Network

Yifan Wang, Yiliang Guo, Rahul Kumar, Madhavan Swaminathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, a neural network embedded Laguerre-FDTD method is proposed to greatly reduce the simulation order needed to recover the field waveform. By taking the lower order basis function coefficients as the training data, numerical results show up to half of the simulation order coefficients can be predicted by the neural network. Both time and frequency-domain (S-parameter) results converted from predicted basis function value show excellent accuracy compared with ground truth.

Original languageEnglish (US)
Title of host publication2024 IEEE/MTT-S International Microwave Symposium, IMS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages473-476
Number of pages4
ISBN (Electronic)9798350375046
DOIs
StatePublished - 2024
Event2024 IEEE/MTT-S International Microwave Symposium, IMS 2024 - Washington, United States
Duration: Jun 16 2024Jun 21 2024

Publication series

NameIEEE MTT-S International Microwave Symposium Digest
ISSN (Print)0149-645X

Conference

Conference2024 IEEE/MTT-S International Microwave Symposium, IMS 2024
Country/TerritoryUnited States
CityWashington
Period6/16/246/21/24

All Science Journal Classification (ASJC) codes

  • Radiation
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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