Simulation study of EIT inverse problem based on Bayesian method

Abstract

The prior of blocky resistivity profile is formulated based on the minimal of total variation using Bayesian method, and the resistivity distribution is reconstructed by Maximum a posteriori (MAP). The Markov chain Monte Carlo (MCMC) method with Gibbs sampler is used to sample from posterior density. The simulations on the 2D model show the feasibility of the method.