Abstract
In this work, a multiplicative regularization scheme is applied to the two-dimensional EIT inversion. In the cost functional, the data misfit is multiplied by a weighted L2-norm-based regularization factor. Gauss-Newton method is used to minimize the cost functional iteratively. In the implementation of the multiplicative regularization scheme, the gradient and divergence operators need to be approximated on triangular meshes. For this purpose, discrete exterior calculus (DEC) theory is applied to rigorously formulate these operators. Numerical examples show a good reconstruction and anti-noise performance of the multiplicative regularization scheme.
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