On bias and its reduction via standardization in discretized electromagnetic source localization problems

Joonas Lahtinen
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引用次数: 1

Abstract

In electromagnetic source localization problems stemming from linearized Poisson-type equation, the aim is to locate the sources within a domain that produce given measurements on the boundary. In this type of problem, biasing of the solution is one of the main causes of mislocalization. A technique called standardization was developed to reduce biasing. However, the lack of a mathematical foundation for this method can cause difficulties in its application and confusion regarding the reliability of solutions. Here, we give a rigorous and generalized treatment for the technique using the Bayesian framework to shed light on the technique's abilities and limitations. In addition, we take a look at the noise robustness of the method that is widely reported in numerical studies. The paper starts by giving a gentle introduction to the problem and its bias and works its way toward standardization.
关于离散化电磁源定位问题中的偏差及其通过标准化减少偏差的问题
在源于线性化泊松类方程的电磁源定位问题中,目的是定位在边界上产生给定测量值的域内的源。在这类问题中,求解偏差是造成定位错误的主要原因之一。为了减少偏差,人们开发了一种名为 "标准化 "的技术。然而,由于这种方法缺乏数学基础,在应用时可能会遇到困难,并在求解的可靠性方面造成混乱。在此,我们使用贝叶斯框架对该技术进行了严格的通用处理,以阐明该技术的能力和局限性。此外,我们还考察了数值研究中广泛报道的该方法的噪声鲁棒性。本文首先温和地介绍了问题及其偏差,然后逐步实现标准化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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