Spectroscopy and Spectral Analysis, Volume. 40, Issue 10, 3061(2020)

Terahertz Spectrum Analysis for Binary Amino Acids Mixture Based on Empirical Mode Decomposition

Jing LIU1...1, Hai-shun LIU1,1, Jian ZUO1,1, Cun-lin ZHANG1,1, Yue-jin ZHAO1,1, and Mei-yan LIANG11 |Show fewer author(s)
Author Affiliations
  • 1[in Chinese]
  • 11. School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China
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    Figures & Tables(6)
    Flowchart of EMD-PLS modeling
    (a) 28 original temporal signals and (b) absorption spectra of 28 original amino acids samples
    EMD decomposed IMFs and residual function of concentration=0% sample
    The corresponding absorption spectra of concentration=0% sample for the first one IMFs (IMF1), two IMFs superposition (IMF1+IMF2), three IMFs superposition (IMF1+IMF2+IMF3), four IMFs superposition (IMF1+IMF2+IMF3+IMF4) and five IMFs superposition (IMF1+IMF2+IMF3+IMF4+IMF5)
    Scatter plots of the actual concentration versus the predicted concentration using (a) PLS model and (b) EMD-PLS model (IMF1+IMF2+IMF3+IMF4) for different concentrations of amino acids mixture samples
    • Table 1. PLS calibration and prediction performance statistics for binary mixtures

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      Table 1. PLS calibration and prediction performance statistics for binary mixtures

      Signal componentsRcalRMSEC
      /%
      RpRMSEP
      /%
      Original signal0.994 60.021 80.990 00.025 1
      IMF1+IMF20.993 20.021 70.991 70.029 0
      IMF1+IMF2+IMF30.995 20.019 20.993 70.022 4
      IMF1+IMF2+IMF3+IMF40.999 40.006 80.996 10.019 8
      IMF1+IMF2+IMF3+IMF4+IMF51.000 00.000 50.990 90.033 0
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    Jing LIU, Hai-shun LIU, Jian ZUO, Cun-lin ZHANG, Yue-jin ZHAO, Mei-yan LIANG. Terahertz Spectrum Analysis for Binary Amino Acids Mixture Based on Empirical Mode Decomposition[J]. Spectroscopy and Spectral Analysis, 2020, 40(10): 3061

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    Paper Information

    Category: Research Articles

    Received: Aug. 16, 2019

    Accepted: --

    Published Online: Jun. 18, 2021

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2020)10-3061-05

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