An Improved Tikhonov Regularization Method for Conductivity Tomography Imaging

Discretizations of inverse problem lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and in order to compute stable solutions to these systems it is necessary to apply regularization methods. This paper compares our improved Tikhonov regularization algorithm to several existing regularization methods, which are carried out to the theoretical mode, and the results prove that this improved method acquires satisfactory result and is superior to other methods. We make use of this improved technique to a practical mode, and the solution is perfect.