Detecting stochastic inclusions in electrical impedance tomography
classification
🧮 math.AP
keywords
anomalyconductivityelectricalimpedancemethodstochastictomographyapplying
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This work considers the inclusion detection problem of electrical impedance tomography with stochastic conductivities. It is shown that a conductivity anomaly with a random conductivity can be identified by applying the Factorization Method or the Monotonicity Method to the mean value of the corresponding Neumann-to-Dirichlet map provided that the anomaly has high enough contrast in the sense of expectation. The theoretical results are complemented by numerical examples in two spatial dimensions.
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