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A survey of the baseline correction algorithms for real-time spectroscopy processing

机译:基线校正算法进行实时光谱处理

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In spectroscopy data analysis, such as Raman spectra, X-ray diffraction, fluorescence and etc., baseline drift is a ubiquitous issue. In high speed testing which generating huge data, automatic baseline correction method is very important for efficient data processing. We will survey the algorithms from classical Shirley background to state-of-the-art methods to present a summation for this specific field. Both advantages and defects of each algorithm are scrutinized. To compare the algorithms with each other, experiments are also carried out under SVM gap gain criteria to show the performance quantitatively. Finally, a rank table of these methods is built and the suggestions for practical choice of adequate algorithms is provided in this paper.
机译:在光谱数据分析中,如拉曼光谱,X射线衍射,荧光等,基线漂移是普遍存在的问题。在产生巨大数据的高速测试中,自动基线校正方法对于高效数据处理非常重要。我们将调查从古典雪莉背景到最先进的方法的算法为此特定领域的求和。仔细审查了每种算法的两个优点和缺陷。为了将算法相互进行比较,在SVM间隙增益标准下还进行实验,以定量地显示性能。最后,建立了这些方法的等级表,本文提供了对现实算法的实际选择的建议。

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