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Calibration Transfer for Near-Infrared (NIR) Spectroscopy Based on Neighborhood Preserving Embedding

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成果类型:
期刊论文
作者:
Chen, Lijuan;Liu, Dawei;Zhou, Jiheng*;Bin, Jun*;Li, Zhen
通讯作者:
Zhou, Jiheng;Bin, Jun
作者机构:
[Zhou, Jiheng; Chen, Lijuan] Hunan Agr Univ, Coll Biosci & Biotechnol, Changsha, Peoples R China.
[Liu, Dawei] Hunan Agr Univ, Coll Engn, Changsha, Peoples R China.
[Bin, Jun] Guizhou Univ, Coll Tobacco Sci, Guiyang 550025, Peoples R China.
[Li, Zhen] Guizhou Tobacco Co, Qianxinan Branch, Xingyi, Peoples R China.
通讯机构:
[Zhou, Jiheng] H
[Bin, Jun] G
Hunan Agr Univ, Coll Biosci & Biotechnol, Changsha, Peoples R China.
Guizhou Univ, Coll Tobacco Sci, Guiyang 550025, Peoples R China.
语种:
英文
关键词:
Calibration transfer;dimensionality reduction;near-infrared spectroscopy (NIR);neighborhood preserving embedding (NPE)
期刊:
Analytical Letters
ISSN:
0003-2719
年:
2021
卷:
54
期:
6
页码:
947-965
基金类别:
This work is financially supported by the Talent Introduction Research Project of Guizhou University (Grant No. [2017]69).
机构署名:
本校为第一且通讯机构
院系归属:
工学院
生物科学技术学院
摘要:
Calibration transfer is a subtle issue in the practical application of near-infrared (NIR) spectroscopy technique. In this paper, a novel method to calibration transfer based on neighborhood preserving embedding (CTNPE) for correcting spectral differences was proposed. As a manifold learning method, neighborhood preserving embedding (NPE) can not only capture the nonlinear manifold structure, but also retain the linearity and show good generalization ability. Since this approach can reveal low dimensional manifold structure in high dimensional spectroscopic data, it is beneficial to construct ...

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