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

Kim, J. H., Kang, B. C., Lee, S. H., Choi, B. Y., Kim, M. C., Kim, B. S., Ijaz, U. Z. , Kim, K. Y. and Kim, S. (2006) Phase boundary estimation in electrical resistance tomography with weighted multi-layered neural networks and front point approach. Measurement Science and Technology, 17(10), pp. 2731-2739. (doi:10.1088/0957-0233/17/10/027)

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Abstract

This work presents a boundary estimation approach in electrical impedance imaging for binary mixture fields based on weighted multi-layered neural network and front point approach. The interfacial boundary is expressed with front points and the unknown front points are estimated with the weighted multi-layered neural network. Numerical experiments show that the proposed electrical resistance imaging approach has a good possibility for the application in the visualization of a binary mixture boundary for real-time monitoring.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ijaz, Dr Umer Zeeshan
Authors: Kim, J. H., Kang, B. C., Lee, S. H., Choi, B. Y., Kim, M. C., Kim, B. S., Ijaz, U. Z., Kim, K. Y., and Kim, S.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:Measurement Science and Technology
Publisher:Institute of Physics Publishing Ltd.
ISSN:0957-0233
ISSN (Online):1361-6501

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