Support vector machine classification of suspect powders using laser-induced breakdown spectroscopy (LIBS) spectral data-Reference-Cited by-同舟云学术

Support vector machine classification of suspect powders using laser-induced breakdown spectroscopy (LIBS) spectral data

Published:2012-04-10 Issue:5 Volume:26 Page:143-149
ISSN:0886-9383
Container-title:Journal of Chemometrics
language:en
Short-container-title:J. Chemometrics

Author:

Cisewski Jessi¹,Snyder Emily²,Hannig Jan¹,Oudejans Lukas²

Affiliation:

1. Department of Statistics and Operations Research; University of North Carolina at Chapel Hill; Chapel Hill; NC; 27599-3260; USA

2. US Environmental Protection Agency, Office of Research and Development; National Homeland Security Research Center; Research Triangle Park; NC; 27711; USA

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cem.2422/fullpdf

Reference22 articles.

1. Detector for trace elemental analysis of solid environmental-samples by laser-plasma spectroscopy;Wisbrun;Anal. Chem.,1994

2. A numerical study of expected accuracy and precision in calibration-free laser-induced breakdown spectroscopy in the assumption of ideal analytical plasma;Tognoni;Spectrochim Acta B,2007

3. Laser beam profile influence on LIBS analytical capabilities: single vs. multimode beam;Lednev;J Anal Atom Spectrom,2010

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