Open AccessA method of characteristic LIF spectral signatures separation based on radial basis function networks
Author(s) -
Hongbin Li,
Wenqing Liu,
Yujun Zhang,
Zhiqun Ding,
Nanjing Zhao,
Qinhua Wei,
Yuping Wang,
Yang Li-Shu
Publication year - 2005
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.54.4451
Subject(s) - dissolved organic carbon , laser induced fluorescence , fluorescence , spectral signature , materials science , separation (statistics) , spectral function , raman spectroscopy , radial basis function , laser , function (biology) , sensitivity (control systems) , analytical chemistry (journal) , biological system , optics , physics , remote sensing , computer science , chemistry , artificial neural network , environmental chemistry , artificial intelligence , geology , engineering , condensed matter physics , machine learning , evolutionary biology , electronic engineering , biology
The separation of characteristic spectral signatures plays an important role in the laser induced fluorescence (LIF) system used for monitoring dissolved organic matter (DOM) in polluted water,which has advantages of high sensitivity,fast detection,remote measurement,etc. In this paper,a method of characteristic spectral signatures separation based on radial basis function networks (RBFN) will be presented. Using this method,we separated the spectral components of laser,Raman and fluorescence of DOM from the LIF spectral. The concentration of DOM in polluted water can be retrieved from the separated spectrums.