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Estimation of the Discrete Spectrum of Relaxations for Electromagnetic Induction Responses Using -Regularized Least Squares for

机译:用正则化最小二乘估计电磁感应响应的离散弛豫谱

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摘要

The electromagnetic induction response of a target can be accurately modeled by a sum of real exponentials. However, in practice, it is difficult to obtain the model parameters from measurements. We previously proposed a constrained linear method that can robustly estimate the model parameters when they are nonnegative. In this letter, we present a modified $ell_{p}$-regularized least squares algorithm, for $0 leq p leq 1$, that eliminates the nonnegative constraint. An empirical method for choosing the regularization parameter is also studied. Using tests on synthetic data and laboratory measurements, the proposed method is shown to provide robust estimates of the model parameters in practice.
机译:目标的电磁感应响应可以通过实指数的总和精确建模。但是,实际上很难从测量中获得模型参数。先前我们提出了一种约束线性方法,该方法可以在模型参数为非负时可靠地估计模型参数。在这封信中,我们提出了一种针对$ 0 leq p leq 1 $的修改后的$ ell_ {p} $-正则化最小二乘算法,该算法消除了非负约束。还研究了选择正则化参数的经验方法。使用对合成数据的测试和实验室测量,表明所提出的方法可以在实践中提供对模型参数的可靠估计。

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