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CLC number: O652.9, O657
On-line Access: 2024-08-27
Received: 2023-10-17
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A NEW COMPUTING MULTIVARIATE SPECTRAL ANALYSIS METHOD BASED ON WAVELET TRANSFORM
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CHENG Yi-yu, CHEN Min-jun. A NEW COMPUTING MULTIVARIATE SPECTRAL ANALYSIS METHOD BASED ON WAVELET TRANSFORM[J]. Journal of Zhejiang University Science A, 2000, 1(1): 15-19.
@article{title="A NEW COMPUTING MULTIVARIATE SPECTRAL ANALYSIS METHOD BASED ON WAVELET TRANSFORM",
author="CHENG Yi-yu, CHEN Min-jun",
journal="Journal of Zhejiang University Science A",
volume="1",
number="1",
pages="15-19",
year="2000",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2000.0015"
}
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%A CHENG Yi-yu
%A CHEN Min-jun
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2000.0015
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A1 - CHENG Yi-yu
A1 - CHEN Min-jun
J0 - Journal of Zhejiang University Science A
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EP - 19
%@ 1869-1951
Y1 - 2000
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2000.0015
Abstract: This paper proposes a new algorithm for multivariate calibration named Principal Component Regression Based on Wavelet (PCRW) which combines wavelet decomposition technique with the factor analysis method for establishing a duplicate denoising mechanism. A practical example in spectral analysis of a typical multicomponent pharmaceutical system was used to verify the effectiveness of the algorithm. It was shown that PCRW produced fewer prediction errors than those obtained by using PCR.
[1]Bao Lunjun, Mo Jinyuan and Jang Zuying, 1997. The application in processing analytical chemistry signal of a cardinal spline approach to wavelets. Anal. Chem. 69: 3053
[2]Bos, M. and Hoogendam, E., 1992. Wavelet transform for the evaluation of peak intensities in flow-injection analysis. Anal. Chim. Acta, 267:73.
[3]Bos, M. and Vrielink, J. A. M., 1994. The wavelet transform for pro-processing IR spectra in the identification of mono and di-Substituted benzenes. Chemom. & Intell. Lab. Syst., 23:115.
[4]Geladi, P., Kowalski, B. R., 1986. Partial lest-squares regression: A tutorial. Anal. Chim. Acta, 185:1.
[5]Halland, D. M. and Thomas, E. V., 1988. Partial least-squares methods for spectral analysis. Anal. Chem., 60:1193.
[6]Henk, L. C. and Thomas, L., 1992. Computer-Enhanced analytical spectroscopy, Volume III. Plenum Press, New York and London, p.1-2.
[7]Lu Xiaoquan, Mo Jingyuan, 1996. Wavelet analysis as a new method in analytical chemometrics. Chinese J. of Anal. Chem., 24: 1100(in Chinese with English abstract).
[8]Mallat, S., 1989. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. Pattern Anal. Machine Intell., 11: 674.
[9]Mallat, S. and Hwang, W. L., 1992. Singularities detection and processing with wavelets. IEEE Trans. on Inform. Theory, 38:617.
[10]Pan Zhongxiao, Si Shengzhu, Nie Shengzhe et al., 1992. Factor analysis in chemistry. Chinese Science and Technology Unversity Press, Hefei, p.184(in Chinese).
[11]Yulong Xie, Kalivas, J. H., 1997. Loal prediction models by principal component regression. Anal. Chim. Acta., 348:29.
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