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Electrical Impedance Tomography, as an Invers Problem, is calculation of the resistivity distribution due ti given boundary potential and current density distribution. MOst of the invers problem are ill-posed, since the measurement data are limited and inperfect. This paper describes a regularization technique for solving the ill-posed problem appeared in the invers 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 is chosen from a-posteriori information during iteration. We made comparison of 3 methods, the first method is a heuristics which can be thought of as discrepancy principle, where we select an initial value of the regularization parameter by trial and error technique. The second and third methods are method s adopted from Linear ill-posed problem, with a posteriori information characters. We present numerically the reconstruction using artificially generated data. |