• DocumentCode
    699637
  • Title

    Stochastic simulation and parameter estimation of first order chemical reactions

  • Author

    De Cock, Katrien ; Xueying Zhang ; Bugallo, Monica F. ; Djuric, Petar M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Stony Brook Univ., Stony Brook, NY, USA
  • fYear
    2004
  • fDate
    6-10 Sept. 2004
  • Firstpage
    1111
  • Lastpage
    1114
  • Abstract
    In this paper, we present fast stochastic simulation methods for the class of first order chemical reactions. The methods are based on the exact distributions for the number of molecules or their Gaussian approximations. Furthermore, using the adopted models, we develop parameter estimation methods for the reaction rates. Although we only discuss two basic reactions, the single channel and reversible first order reactions, the obtained results can be applied to more complex cases.
  • Keywords
    approximation theory; chemical reactions; parameter estimation; reaction kinetics; stochastic processes; Gaussian approximations; adopted models; fast stochastic simulation methods; first order chemical reactions; parameter estimation methods; reaction rates; reversible first order reactions; single channel reactions; Abstracts; Approximation methods; Artificial neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2004 12th European
  • Conference_Location
    Vienna
  • Print_ISBN
    978-320-0001-65-7
  • Type

    conf

  • Filename
    7080167