scholarly journals Pretreatment and Wavelength Selection Method for Near-Infrared Spectra Signal Based on Improved CEEMDAN Energy Entropy and Permutation Entropy

Entropy ◽  
2017 ◽  
Vol 19 (7) ◽  
pp. 380 ◽  
Author(s):  
Xiaoli Li ◽  
Chengwei Li
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Selection Method ◽  
Permutation Entropy ◽  
Wavelength Selection ◽  
Energy Entropy ◽  
Near Infrared Spectra

Spectral transformation and wavelength selection in near-infrared spectra classification

1995 ◽  
Vol 315 (3) ◽  
pp. 243-255 ◽  
Author(s):  
W. Wu ◽  
B. Walczak ◽  
D.L. Massart ◽  
K.A. Prebble ◽  
I.R. Last
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Wavelength Selection ◽  
Spectral Transformation ◽  
Near Infrared Spectra

scholarly journals New Indicator for Optimal Preprocessing and Wavelength Selection of Near-Infrared Spectra

2004 ◽  
Vol 58 (3) ◽  
pp. 264-271 ◽  
Author(s):  
E. T. S. Skibsted ◽  
H. F. M. Boelens ◽  
J. A. Westerhuis ◽  
D. T. Witte ◽  
A. K. Smilde
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Wavelength Selection ◽  
Near Infrared Spectra ◽  
Selection Of

Assessment of Partial Least-Squares Calibration and Wavelength Selection for Complex Near-Infrared Spectra

1998 ◽  
Vol 52 (6) ◽  
pp. 878-884 ◽  
Author(s):  
Michael J. McShane ◽  
Gerard L. Coté ◽  
Clifford H. Spiegelman
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Wavelength Selection ◽  
Absorption Bands ◽  
Full Spectrum ◽  
Single Spectrum ◽  
Near Infrared Spectra ◽  
Selection For

Complex near-infrared (near-IR) spectra of aqueous solutions containing five independently varying absorbing species were collected to assess the ability of partial least-squares (PLS) regression and wavelength selection for calibration and prediction of these species in the presence of each other. It was confirmed that PLS calibration models can successfully predict chemical concentrations of all five chemicals from a single spectrum. It was observed from the PLS spectral loadings that spectral regions containing absorption bands of a single analyte alone were not sufficient for the model to adequately predict the concentration of the analyte because of the high degree of overlap between glucose, lactate, ammonia, glutamate, and glutamine. Three wavelength selection algorithms were applied to the spectra to identify regions containing necessary information, and in each case it was found that nearly the entire spectral range was needed for each determination. The results suggest that wavelength selection does result in a reduction of data points from the full spectrum, but the decrease seen with these near-infrared spectra was less than typically seen in mid-IR or Raman spectra, where peaks are narrower and well separated. As a result of this need for more wavelengths, the engineering of a dedicated system to measure these analytes in complex media such as blood or tissue culture broths by using this near-infrared region (2.0–2.5 μm) is further complicated.

Sign in / Sign up

Export Citation Format

Share Document