제어로봇시스템학회:학술대회논문집

제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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Boundary estimation in electrical impedance tomography with multi-layer neural networks

  • Kim, Jae-Hyoung (Department of Electronic Engineering, Kyungpook National University) ;
  • Jeon, Hae-Jin (Department of Electronic Engineering, Kyungpook National University) ;
  • Choi, Bong-Yeol (Department of Electronic Engineering, Kyungpook National University) ;
  • Lee, Seung-Ha (Department of Electronic Engineering, Kyungpook National University) ;
  • Kim, Min-Chan (Department of Chemical Engineering, Cheju National University) ;
  • Kim, Sin (Department of Nuclear & Energy Engineering, Cheju National University) ;
  • Kim, Kyung-Youn (Department of Electrical and Electronic Engineering, Cheju National University)
  • 발행 : 2004.08.25
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초록

This work presents a boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a parallel structured multi-layer neural network. The interfacial boundaries are expressed with the truncated Fourier series and the unknown Fourier coefficients are estimated with the parallel structure of multi-layer neural network. Results from numerical experiments shows that the proposed approach is insensitive to the measurement noise and has a strong possibility in the visualization of binary mixtures for a real time monitoring.

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