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Baseline correction based on L1-Norm optimization and its verification by a computer vision method

机译:基于L1-Norm优化的基线校正及其计算机视觉方法的验证

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摘要

Baseline correction in time series of ground motion is a challenging problem in research pertaining to strong ground motion. In previous studies in this area, numerous methods have been proposed to identify baseline drift. However, there is no systematic approach to verify the proposed methods. In this paper, we propose a vision-based approach to evaluate baseline correction methods quantitatively. In addition, for our proposed baseline correction method based on L1-norm optimization, we analyze the method in detail and provide a thorough analysis of the method based on experimental data. From the comparison, our method shows good performance in recovering the baseline.
机译:地震动时间序列的基线校正是与强地震动有关的研究中的一个难题。在该领域的先前研究中,已经提出了许多方法来识别基线漂移。但是,没有系统的方法来验证所提出的方法。在本文中,我们提出了一种基于视觉的方法来定量评估基线校正方法。此外,对于我们提出的基于L1-范数优化的基线校正方法,我们将对方法进行详细分析,并根据实验数据对该方法进行全面的分析。通过比较,我们的方法在恢复基线方面显示出良好的性能。

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