基于自适应相关向量机的层析成像传感器自动重构

2019 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM) Pub Date : 1900-01-01 DOI:10.23919/USNC-URSI-NRSM.2019.8713113

Daniel Ospina Acero, S. Chowdhury, F. Teixeira, Q. Marashdeh

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引用次数: 3

摘要

我们应用自适应相关向量机从所有测量元素的排列或组合中自动选择层析成像设置中的测量集，从而产生对估计结果的最低不确定性，同时保持良好的图像重建。为了说明所提出的方法，我们给出了电容层析成像的仿真结果。

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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Automatic Sensor Reconfiguration based on Adaptive Relevance Vector Machine for Uncertainty Reduction in Tomography Imaging

We apply the Adaptive Relevance Vector Machine to automatically select the measurement set in a tomographic setting, from all the arrangements or combinations of the measuring elements, that yield the lowest level of uncertainty about the estimated results, while maintaining good image reconstruction. To illustrate the proposed method, we present simulation results derived from Electrical Capacitance Tomography.

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来源期刊

2019 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)

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