title: Application of wavelet transform to extract the relevant component from spectral data for multivariate calibration.
abstract: An approach aiming at extracting the relevant component for multivariate calibration is introduced, and its performance is compared with the "uninformative variable elimination" approach and with the standard PLS method for the modeling of near-infrared data. The extraction of the relevant component is carried out in the wavelet domain. The PLS results on these relevant features are better, and therefore, it seems that this approach can successfully be used to remove noise and irrelevant information from spectra for multivariate calibration.
authors.affiliation: ChemoAC, Pharmaceutical Institute, Vrije Unversiteit Brussel, Laarbeeklaan 103, B-1090 Brussels, Belgium, and Shell Research and Technology Center, Shell International Chemicals B. V., P.O. Box 38000, 1030 BN Amsterdam, The Netherlands.
authors.forename: D
authors.initials: D
authors.lastname: Jouan-Rimbaud
authors.forename: B
authors.initials: B
authors.lastname: Walczak
authors.forename: R J
authors.initials: RJ
authors.lastname: Poppi
authors.forename: O E
authors.initials: OE
authors.lastname: de Noord
authors.forename: D L
authors.initials: DL
authors.lastname: Massart