Component recognition of 3D fluorescence spectra based on wavelet analysis and weighted least square regression

Author

Xiaoya Yu ; Yujun Zhang ; Changhua Lu ; Huanbo Wang ; Gaofang Yin ; Shaohui Yu ; Yi Zhou ; Wei Zhang ; Rong Zhang

Author_Institution

Key Lab. of Environ. Opt. & Technol., Anhui Inst. of Opt. & Fine Mech., Hefei, China

fYear

2012

fDate

7-9 Dec. 2012

Firstpage

1

Lastpage

4

Abstract

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 demonstrated that wavelet analysis combined with weighted least square regression provides an effective method for component recognition of multi-component three-dimensional fluorescence spectra.

Keywords

fluorescence spectroscopy; mesh generation; regression analysis; signal detection; signal processing; wavelet transforms; 3D fluorescence spectra; Delaunay triangulation interpolation; coif2 wavelet; component recognition; discrimination method; multicomponent three-dimensional fluorescence spectra; signal processing; wavelet analysis; weighted least square regression; Component recognition; Organic matters; Three-dimensional fluorescence spectra; Wavelet analysis; Weighted least square regression;

fLanguage

English

Publisher

iet

Conference_Titel

Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on

Conference_Location

Shenzhen

Electronic_ISBN

978-1-84919-641-3

Type

conf

DOI

10.1049/cp.2012.2301

Filename

6755680