Multi-layer Permittivity Measurement Based on Complementary Split-Ring Resonator and Neural Networks

Chung En Yu, Chin Lung Yang

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

Abstract

A neural network-based method for multi-layer permittivity measurement is proposed in this paper. This method uses the multiple-square concentric complementary split-ring resonator (CSRR) to take multiple non-identical resonance frequency measurement, and a scalable, iterative neural network approach is applied to estimate for dielectric property measurement. Instead of the tedious development and establishment of analytic formulas, neural network engine solver can simplify this step and still have acceptable accuracy. The dual-layer MUTs measurement had an average error of 8.78% for ?1 and an average error of 8.9% for ?2. It can be extended to the measurement of more than two layers substrate.

Original languageEnglish
Title of host publicationProceedings - 2020 International Workshop on Electromagnetics
Subtitle of host publicationApplications and Student Innovation Competition, iWEM 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728199894
DOIs
Publication statusPublished - 2020 Aug 26
Event2020 International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2020 - Penghu, Taiwan
Duration: 2020 Aug 262020 Aug 28

Publication series

NameProceedings - 2020 International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2020

Conference

Conference2020 International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2020
CountryTaiwan
CityPenghu
Period20-08-2620-08-28

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Instrumentation

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