| dc.description.abstract | Electrical Impedance Tomography, as an Inverse Problem, is calculation of the resistivity distribution due to given boundary potential and current density distribution. Most of the inverse problem are ill-posed, since the measurement data are limited and imperfect. This paper describes a regularization technique for solving the ill-posed problem appeared in the inverse EIT. In this regularization technique, a smoothing function with a regularization parameter, is penalizing the objective function in order to obtain a regularized resistivity update equation. The regularization parameter can be chosen from a-posteriori information. We made comparison of 3 methods, the rst method can be thought of as a discrepancy principle, where we select an initial value of the regularization parameter by trial and error technique. The second and third methods are methods adopted from Linear ill-posed problem, with a posteriori information characters. We presents numerically the reconstruction using arti cially generated data. | id |
