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Owing to its low cost, fast response, noninvasiveness, and non-radiation, electrical impedance tomography (EIT) has been applied to numerous fields. However, its spatial resolution is low due to the inherent ill-posed problem and the “soft field” effect. The Lpregularization (02to its variants L1and L1/2. Nevertheless, Lpregularization is generally difficult to be solved fast and efficiently, and the selection of p yielding the best result is also a problem. In this paper, an adaptive re-weighted (ARW) algorithm with a general frame is presented to solve the Lpregularization for EIT, with p for each pixel determined adaptively in iterations. Experiments were carried out to validate the proposed algorithm. Results show that compared with other EIT algorithms, the ARW algorithm had a higher spatial resolution. Moreover, it can provide a wider range of selection for regularization parameter, which increases the practicality of the proposed algorithm.
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Li et al. (2019) studied this question.
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