Phase boundary estimation in electrical resistance tomography with weighted multi-layer neural networks and front point approach

J. H. Kim, B. C. Kang, B. Y. Choi, S. H. Lee, M. C. Kim, B. S. Kim, K. Y. Kim, S. Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work presents a complex boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a weighted multi-layer neural network and front point approach. The interfacial boundary expressed with front points and the unknown front points are estimated with the weighted multi-layer neural netwrok. Results from numerical experiments show that the proposed approach is insensitive to the measurement noise and has a strong good possibility for application in the visualization of binary mixtures for real time monitoring.

Original languageEnglish
Title of host publication4th World Congress in Industrial Process Tomography
PublisherInternational Society for Industrial Process Tomography
Pages410-415
Number of pages6
ISBN (Electronic)9780853163206
StatePublished - 2005
Event4th World Congress in Industrial Process Tomography - Aizu, Japan
Duration: 5 Sep 20055 Sep 2005

Publication series

Name4th World Congress in Industrial Process Tomography

Conference

Conference4th World Congress in Industrial Process Tomography
Country/TerritoryJapan
CityAizu
Period5/09/055/09/05

Keywords

  • Boundary estimation
  • Front point tracking
  • Multi-layer neural network

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