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综述化学计量学结合拉曼光谱在生物材料检测中的应用。报道利用基线校正方法(导数、曲线拟合、小波变换)、归一化方法(矢量归一化、峰高归一化)、复合预处理等方法,可以提高信噪比,恢复失真的信号,实现谱图峰位的正确识别;基于主成分分析、偏最小二乘、聚类分析、目标因子分析、人工神经网络、支持向量机等算法构建化学计量模型,利用模型对拉曼光谱定性或定量分析,分别得到可信的结果;提出未来化学计量建模的方向。
Summary The application of chemometrics combined with Raman spectroscopy in the detection of biomaterials. The report can improve the signal-to-noise ratio and recover the distorted signals by using the methods of baseline correction (derivative, curve fitting, wavelet transform), normalization methods (vector normalization and peak height normalization) and composite preprocessing, To achieve the correct identification of the peak position of the spectrum; to construct the stoichiometric model based on the principal component analysis, partial least-squares, cluster analysis, target factor analysis, artificial neural network, support vector machine and other algorithms, to use the model to qualitative or quantitative Raman spectroscopy Analysis, respectively, to get credible results; put forward the future direction of stoichiometry modeling.