Authors: Jung, Young Mee; Shin, Hyeon Suk; Kim, Seung Bin; Noda, Isao

Source: Applied Spectroscopy, Volume 56, Issue 12, Pages 329A-344A and 1515-1632 (December 2002) , pp. 1562-1567(6)

Publisher: Society for Applied Spectroscopy

Abstract:

The direct combination of chemometrics and two-dimensional (2D) correlation spectroscopy is considered. The use of a reconstructed data matrix based on the signifi cant scores and loading vectors obtained from the principal component analysis (PCA) of raw spectral data is proposed as a method to improve the data quality for 2D correlation analysis. The synthetic noisy spectra were analyzed to explore the novel possibility of the use of PCA-reconstructed spectra, which are highly noise suppressed. 2D correlation analysis of this reconstructed data matrix, instead of the raw data matrix, can significantly reduce the contribution of the noise component to the resulting 2D correlation spectra.

Keywords: INDEX HEADINGS TWO-DIMENSIONAL 2D CORRELATION SPEC; PRINCIPAL COMPONENT ANALYSIS; PCA; PCA 2D CORRELATION SPECTROSCOPY

Document Type: Miscellaneous

DOI: http://dx.doi.org/10.1366/000370202321116020

Publication date: 2002-12-01

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