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Influence of signal-to-noise ratio on accuracy of spectral analysis by near infrared spectroscopy 被引量:1
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作者 ZHUANG Xin-gang SHI Xue-shun +3 位作者 LIU Hong-bo LIU Chang-ming ZHANG Peng-ju WANG Heng-fei 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2020年第3期211-216,共6页
As one of the important indicators of spectrometer,signal-to-noise ratio(SNR)reflects the ability of spectrometer to detect weak signals.To investigate the influence of SNR on the prediction accuracy of spectral analy... As one of the important indicators of spectrometer,signal-to-noise ratio(SNR)reflects the ability of spectrometer to detect weak signals.To investigate the influence of SNR on the prediction accuracy of spectral analysis,we first introduce the major factors affecting the spectral SNR.Taking green tea as an example,the influence of spectral SNR on the prediction accuracy of the origin identification model is analyzed by experiments.At the same time,the relationship between the spectral SNR and prediction accuracy of spectral analysis model is fitted.Based on this,the common methods for improving the spectral SNR are discussed.The results show that the accuracy of the prediction set model first decreases slowly,then decreases linearly,and finally tends to be flat as the spectral SNR decreases.Through calculation,in order to achieve the prediction accuracy of prediction model reaching 90%and 85%,the spectral SNR is required to be higher than 23.42 dB and 21.16 dB,respectively.The overall results provide certain parameters support for the development of new online analytical spectroscopic instruments,especially for the technical indicators of SNR. 展开更多
关键词 near infrared spectroscopy signal-to-noise ratio(SNR) partial least squares(PLS) spectral analysis green tea
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