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A non-iterative method for the electrical impedance tomography based on joint sparse recovery

机译:基于联合稀疏恢复的电阻抗层析成像非迭代方法

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The purpose of this paper is to propose a non-iterative method for the inverse conductivity problem of recovering multiple small anomalies from the boundary measurements. When small anomalies are buried in a conducting object, the electric potential values inside the object can be expressed by integrals of densities with a common sparse support on the location of anomalies. Based on this integral expression, we formulate the reconstruction problem of small anomalies as a joint sparse recovery and present an efficient non-iterative recovery algorithm of small anomalies. Furthermore, we also provide a slightly modified algorithm to reconstruct an extended anomaly. We validate the effectiveness of the proposed algorithm over the linearized method and the multiple signal classification algorithm by numerical simulations.
机译:本文的目的是为从边界测量中恢复多个小异常的反电导率问题提出一种非迭代方法。当小的异常被掩埋在导电物体中时,物体内部的电势值可以由密度的积分表示,并具有对异常位置的共同稀疏支持。基于该积分表达式,我们将小异常的重建问题公式化为联合稀疏恢复,并提出了一种有效的小异常的非迭代恢复算法。此外,我们还提供了稍微修改的算法来重构扩展的异常。通过数值模拟,我们验证了所提算法优于线性化方法和多信号分类算法的有效性。

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