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Kvantovaya Elektronika, 2001, Volume 31, Number 9, Pages 834–838 (Mi qe2056)  

This article is cited in 7 scientific papers (total in 7 papers)

Laser applications and other topics in quantum electronics

Laser fluorimetry of mixtures of polyatomic organic compounds using artificial neural networks

S. A. Dolenkoa, I. V. Gerdovab, T. A. Dolenko (Gogolinskaya)b, V. V. Fadeevb

a Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University
b Lomonosov Moscow State University, Faculty of Physics
Full-text PDF (178 kB) Citations (7)
Abstract: New possibilities of laser fluorimetry offered by the use of algorithms for solving inverse problems based on artificial neural networks are demonstrated. A two-component mixture of polyatomic organic compounds is analysed by three methods of laser fluorimetry: a direct analysis of the fluorescence band, the kinetic fluorimetry (when durations of the laser pulse and the detector gate pulse are comparable with the fluorescence lifetimes or exceed them), and the saturation fluorimetry. The numerical experiments showed that the use of artificial neural networks in these methods provides a high practical stability of the solution of inverse problems and ensures a high sensitivity and a high accuracy of determining the contribution of components to fluorescence and of measuring molecular photophysical parameters, which can be used for the identification of components.
Received: 29.03.2001
English version:
Quantum Electronics, 2001, Volume 31, Issue 9, Pages 834–838
DOI: https://doi.org/10.1070/QE2001v031n09ABEH002056
Bibliographic databases:
Document Type: Article
PACS: 33.50.Dq, 07.05.Mh
Language: Russian


Citation: S. A. Dolenko, I. V. Gerdova, T. A. Dolenko (Gogolinskaya), V. V. Fadeev, “Laser fluorimetry of mixtures of polyatomic organic compounds using artificial neural networks”, Kvantovaya Elektronika, 31:9 (2001), 834–838 [Quantum Electron., 31:9 (2001), 834–838]
Linking options:
  • https://www.mathnet.ru/eng/qe2056
  • https://www.mathnet.ru/eng/qe/v31/i9/p834
  • This publication is cited in the following 7 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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