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

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.