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Fluorescence spectroscopy is a rapid and non-destructive method for monitoring water quality. In this work, wavelet analysis, together with independent component analysis (ICA), was applied for component recognition of seriously overlapped, multi-component, three dimensional fluorescence spectra. Wavelet analysis extracts the features of the spectra and amplifies differences among phenolic homologs...
Wavelet analysis is widely used in signal processing. It is applied to the component recognition of multi-component three-dimensional fluorescence spectra in this paper. After the scattering peaks removed by the delaunay triangulation interpolation, the fluorescence spectra are transformed with the coif2 wavelet and the discrimination method is established by weighted least square regression. It is...
The accuracy of spectrum preprocessing, as the precondition of precise qualitative and quantitative spectrum analysis, performs importantly. This paper presents a new approach of combining wavelet transform (WT) with principal component analysis (PCA) in the preprocessing of spectrum analysis. The multi-scale characteristic of WT in time and frequency domain is utilized to extract useful signals and...
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