A Background and noise elimination method for quantitative calibration of near infrared spectra
A new hybrid algorithm is proposed to eliminate the varying background and noise simultaneously for multivariate calibration of near infrared (NIR) spectral signals. The method is based on the use of multi-resolution, which is one of the main advantages provided by wavelet transform. The signals are...
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| Published in | Analytica chimica acta Vol. 511; no. 1; pp. 37 - 45 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
24.05.2004
Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | A new hybrid algorithm is proposed to eliminate the varying background and noise simultaneously for multivariate calibration of near infrared (NIR) spectral signals. The method is based on the use of multi-resolution, which is one of the main advantages provided by wavelet transform. The signals are firstly split into different frequency components, which keep the same data points of the original signals. In conjunction with a modified uninformative variable elimination (mUVE) criterion, the new method can be used to remove the low-frequency varying background and the high-frequency noise simultaneously. The method is successfully applied to simulated spectral data set and experimental NIR spectral data, resulting in more parsimonious multivariate models with higher precision. In addition, the proposed strategy can be applied to other spectral signals as well. |
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| AbstractList | A new hybrid algorithm is proposed to eliminate the varying background and noise simultaneously for multivariate calibration of near infrared (NIR) spectral signals. The method is based on the use of multi-resolution, which is one of the main advantages provided by wavelet transform. The signals are firstly split into different frequency components, which keep the same data points of the original signals. In conjunction with a modified uninformative variable elimination (mUVE) criterion, the new method can be used to remove the low-frequency varying background and the high-frequency noise simultaneously. The method is successfully applied to simulated spectral data set and experimental NIR spectral data, resulting in more parsimonious multivariate models with higher precision. In addition, the proposed strategy can be applied to other spectral signals as well. |
| Author | Hu, Bin Chen, Da Su, Qingde Shao, Xueguang |
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| Keywords | Near infrared spectroscopy Wavelet transform Varying background Noise Near infrared spectrometry Wavelet transformation Elimination Calibration Multivariate analysis Background noise Algorithm |
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| SubjectTerms | Analytical chemistry Chemistry Exact sciences and technology Near infrared spectroscopy Noise Spectrometric and optical methods Varying background Wavelet transform |
| Title | A Background and noise elimination method for quantitative calibration of near infrared spectra |
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