Electrical impedance imaging of binary mixtures with boundary estimation approach based on multilayer neural network

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