Institute of Automation, Chinese Academy of Sciences, Beijing, PR China.
Spectrochim Acta A Mol Biomol Spectrosc. 2011 Apr;78(4):1315-20. doi: 10.1016/j.saa.2011.01.004. Epub 2011 Jan 13.
A calibration transfer method for near-infrared (NIR) spectra based on spectral regression is proposed. Spectral regression method can reveal low dimensional manifold structure in high dimensional spectroscopic data and is suitable to transfer the NIR spectra of different instruments. A comparative study of the proposed method and piecewise direct standardization (PDS) for standardization on two benchmark NIR data sets is presented. Experimental results show that spectral regression method outperforms PDS and is quite competitive with PDS with background correction. When the standardization subset has sufficient samples, spectral regression method exhibits excellent performance.
提出了一种基于光谱回归的近红外(NIR)光谱定标传递方法。光谱回归方法可以揭示高维光谱数据中的低维流形结构,适用于传递不同仪器的 NIR 光谱。本文对所提出的方法和分段直接标准化(PDS)在两个基准 NIR 数据集上的标准化进行了比较研究。实验结果表明,光谱回归方法优于 PDS,并且与具有背景校正的 PDS 相当。当标准化子集具有足够的样本时,光谱回归方法表现出优异的性能。