Abstract
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. ICA analysis in blind signal separation was used to separate single component before multiple linear regression (MLR). The proposed method increases the correct classification rate and enriches the spectra library. As such, it is a useful alternative to traditional techniques in component recognition.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callSimilar Papers
More From: Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
