Statistical performance comparison between the FSV and the FS-NMI index

M. Azpúrua, E. Paez, X. Parra, Ferran Silva, R. Jaúregui
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引用次数: 1

Abstract

This paper presents a performance comparison between two validation methods developed specifically for the Computational Electromagnetics purposes: the Feature Selective Validation (FSV) and the Feature Selective Normalized Mutual Information (FSNMI) index. To achieve this goal, a statistical analysis of 40 different cases of study (pairs of data sets) is carried out covering a wide range of real-life applications, such as, frequency domain, noisy and transient data, among others. The results provided an insight of the relationships between each method, showing that more effort is required to achieve generally coherent validation results between the FSV and the FSNMI.
FSV与FS-NMI指数的统计性能比较
本文介绍了专门为计算电磁学目的开发的两种验证方法:特征选择验证(FSV)和特征选择归一化互信息(FSNMI)索引之间的性能比较。为了实现这一目标,对40个不同的研究案例(数据集对)进行了统计分析,涵盖了广泛的现实应用,如频域、噪声和瞬态数据等。结果揭示了每种方法之间的关系,表明需要更多的努力才能在FSV和FSNMI之间获得普遍一致的验证结果。
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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