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- W1555244037 abstract "In electrical impedance tomography (EIT) the internal electrical conductivity can be reconstructed from voltage measurements on the surface of an object under study. The EIT reconstruction problem is a nonlinear ill-posed in-verse problem, and special approaches must be implemented to recover a stable solution. As EIT is an ill-posed problem, small perturbations in the measured boundary voltages can cause arbitrarily large errors in the estimated internal electrical conductivity. Hence, in this situation it is difficult to obtain a satisfactory solution from the nonlinear and ill-posed EIT problem. So it is necessary to use regularization techniques because of the ill-posed nature of the problem. In this paper, we introduce the regularization problem as a quadratic constrained least squares problem. In the area of optimization this problem is a special case of trust-region methods, which is known as the trust-region subproblem (TRS) (Bjorck,1996). A comprehensive study regarding different approaches for solving the regularization problem as a trust-region subproblem is given in (Rojas, 1998). We adopted the recently devel-oped method for solving the trust-region subproblem in the regularization case (Grodzevich, 2004) for the EIT prob-lem. In this method the regularized solution was obtained using a parameterized trust region approach to estimate the region of maximum curvature of the L-curve." @default.
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- W1555244037 date "2008-01-01" @default.
- W1555244037 modified "2023-09-25" @default.
- W1555244037 title "A trust region method for EIT application for human brain" @default.
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