Better and Faster Spectra Analysis Using Analytical Programming on CUDA

  • Peter Drábik
  • Petr Šaloun
  • Ivan Zelinka
  • Marie Vraná
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 289)


In this paper we discuss a method useful for spectra analysis – analytical programming and its implementation. Our goal is to create mathematical formulas of emission lines from spectra, which are characteristic for Be stars. One issue in performing this task is symbolic regression, which represents the process in our application, when measured data fit the best represented mathematical formula. In past this was only a human domain; nowadays, there are computer methods, which allow us to do it more or less effectively. A novel method in symbolic regression, compared to genetic programming and grammar evolution, is analytic programming. The aim of this work is to verify the efficiency of the parallel approach of this algorithm, using CUDA architecture.


analytical programming spectra analysis CUDA evolutionary algorithm differential evolution parallel implementation symbolic regression 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Peter Drábik
    • 1
  • Petr Šaloun
    • 1
  • Ivan Zelinka
    • 1
  • Marie Vraná
    • 1
  1. 1.VŠB-Technical University of OstravaOstrava-PorubaCzech Republic

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