Fuzzy assisted parameter selection rule in regularized newton algorithm of Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) is an imaging technique which is able to reconstruct an image of the distribution of electrical properties of medium such as resistivity from knowledge of the boundary voltage and current on the object. Almost all EIT image reconstruction problems are ill-posed. We employ the well-known Tikhonov regularization method to solve the ill-posed problem. We introduce a stabilizing function with a regularization parameter to the objective function. By minimizing the objective function, we obtain a regularized resistivity update equation. The problem is how to select a proper regularization parameter in order to find the solution. This study proposed a selection rule of parameter based on the fuzzy logic. To illustrate the proposed method, we present numerically the image reconstruction using artificially generated data.