Component recognition with three-dimensional fluorescence spectra based on non-negative matrix factorization

Non‐negative matrix factorization (NMF) is a widely used approach in signal processing. In this work, we apply it to the component recognition of mixtures with multicomponent three‐dimensional fluorescence spectra. Compared with the popular PARAFAC for component recognition, NMF has the following ad...

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Bibliographic Details
Published in:Journal of chemometrics 2011-11, Vol.25 (11), p.586-591
Main Authors: Yu, Shaohui, Zhang, Yujun, Liu, Wenqing, Zhao, Nanjing, Xiao, Xue, Yin, Gaofang
Format: Article
Language:English
Subjects:
Chemistry
Chemometrics
component recognition
Decomposition
Exact sciences and technology
Factorization
Fluorescence
General and physical chemistry
General. Nomenclature, chemical documentation, computer chemistry
integrated similarity index
Matrix
non-negative matrix factorization
Recognition
Signal processing
Similarity
Spectra
Spectrum analysis
Statistical methods
Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry
Three dimensional
Three dimensional imaging
three-dimensional fluorescence spectra
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Summary:Non‐negative matrix factorization (NMF) is a widely used approach in signal processing. In this work, we apply it to the component recognition of mixtures with multicomponent three‐dimensional fluorescence spectra. Compared with the popular PARAFAC for component recognition, NMF has the following advantages: on one hand, the decomposed spectra are three dimensional, and thus, more information can be obtained, which is beneficial for component recognition; on the other hand, the decomposed spectra are non‐negative and thus have a certain physical significance. More importantly, we propose a type of integrated similarity indices for the three‐dimensional fluorescence spectra, which, by construction, is good at component recognition from overlapping fluorescence spectra. Experiment results demonstrate that NMF combined with integrated similarity index provides an effective method for component recognition of multicomponent three‐dimensional overlapping fluorescence spectra. Copyright © 2011 John Wiley & Sons, Ltd. Non‐negative matrix factorization (NMF) is applied to the component recognition of mixtures with multicomponent three‐dimensional fluorescence spectra. Meanwhile, a type of integrated similarity indices for the three‐dimensional fluorescence spectra is proposed. Experiment results demonstrate that NMF combined with integrated similarity index provides an effective method for component recognition with multicomponent three‐dimensional overlapping fluorescence spectra.
ISSN:0886-9383
1099-128X
1099-128X
DOI:10.1002/cem.1404