Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2006

AUTHORS

Esteban García-Cuesta , Inés M. Galván , Antonio J. de Castro

ABSTRACT

The use of high spectral resolution measurements to obtain a retrieval of certain physical properties related with the radiative transfer of energy leads a priori to a better accuracy. But this improvement in accuracy is not easy to achieve due to the great amount of data which makes difficult any treatment over it and it’s redundancies. To solve this problem, a pick selection based on principal component analysis has been adopted in order to make the mandatory feature selection over the different channels. In this paper, the capability to retrieve the temperature profile in a combustion environment using neural networks jointly with this spectral high resolution feature selection method is studied. More... »

PAGES

754-762

References to SciGraph publications

  • 1989-12. Approximation by superpositions of a sigmoidal function in MATHEMATICS OF CONTROL, SIGNALS, AND SYSTEMS
  • Book

    TITLE

    Intelligent Data Engineering and Automated Learning – IDEAL 2006

    ISBN

    978-3-540-45485-4
    978-3-540-45487-8

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/11875581_91

    DOI

    http://dx.doi.org/10.1007/11875581_91

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1007915074


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