By Martin Simon
This monograph is anxious with the research and numerical answer of a stochastic inverse anomaly detection challenge in electric impedance tomography (EIT). Martin Simon reports the matter of detecting a parameterized anomaly in an isotropic, desk bound and ergodic conductivity random box whose realizations are speedily oscillating. For this objective, he derives Feynman-Kac formulae to scrupulously justify stochastic homogenization with regards to the underlying stochastic boundary price challenge. the writer combines strategies from the idea of partial differential equations and sensible research with probabilistic principles, paving find out how to new mathematical theorems that could be fruitfully utilized in the remedy of the matter handy. additionally, the writer proposes a good numerical technique within the framework of Bayesian inversion for the sensible answer of the stochastic inverse anomaly detection challenge.