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Data mining of spectral data

  • Analysis and Synthesis of Signals and Images
  • Published:
Optoelectronics, Instrumentation and Data Processing Aims and scope

Abstract

This paper describes the Spektran software system intended for automated analysis of object-attribute data tables which implements data mining algorithms based on a function of rival similarity (FRiS). The Spektran system is used to analyze a set of objects (microparticles of a substance) described by spectral characteristics. The following basic problems of data mining are solved: particle clustering by similarity of their spectra, selection of the subset of the most informative spectrum channels, identifying the classes to which particles and their mixes belong and some others.

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Author information

Authors and Affiliations

  1. Institute of Criminalistics, Federal Security Service, Russian Federation, Moscow, Russia

    A. B. Bogdanov, A. V. Kuchkin & M. A. Meshcheryakov

  2. Sobolev Institute of Mathematics, Siberian Branch, Russian Academy of Sciences, pr. Akademika Koptyuga 4, Novosibirsk, 630090, Russia

    I. A. Borisova, N. G. Zagoruiko & O. A. Kutnenko

  3. Novosibirsk State University, ul. Pirogova 2, Novosibirsk, 630090, Russia

    V. V. Dyubanov

  4. OJSC MMC Norilsk Nikel, Tverskoi bul’v. 13, Moscow, 125593, Russia

    N. G. Milovzorov

Authors
  1. A. B. Bogdanov
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  2. I. A. Borisova
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  3. V. V. Dyubanov
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  4. N. G. Zagoruiko
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  5. O. A. Kutnenko
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  6. A. V. Kuchkin
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  7. M. A. Meshcheryakov
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  8. N. G. Milovzorov
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Corresponding author

Correspondence to N. G. Zagoruiko.

Additional information

Original Russian Text © A.B. Bogdanov, I.A. Borisova, V.V. Dyubanov, N.G. Zagoruiko, O.A. Kutnenko, A.V. Kuchkin, M.A. Meshcheryakov, N.G. Milovzorov, 2009, published in Avtometriya, 2009, Vol. 45, No. 1, pp. 92–101.

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Bogdanov, A.B., Borisova, I.A., Dyubanov, V.V. et al. Data mining of spectral data. Optoelectron.Instrument.Proc. 45, 62–69 (2009). https://doi.org/10.1134/S8756699009010105

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  • DOI: https://doi.org/10.1134/S8756699009010105

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