• DocumentCode
    1933200
  • Title

    Dissipativity in Mean Square of Stochastic Reaction Diffusion Systems

  • Author

    Zhang, Yu-tian ; Luo, Qi

  • Author_Institution
    Nanjing Univ. of Inf. Sci. & Technol., Nanjing
  • Volume
    5
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    2639
  • Lastpage
    2644
  • Abstract
    It is by means of Lyapunov method that stochastic ordinary differential equations and stochastic functional differential equations have been studied intensively. However, for stochastic reaction diffusion equations, this useful technique seems to find no way out on account of the empty of its own Ito´s formula. To get over this difficulty, we will regard the integral of the considered trajectory with respect to spatial variables as the solution of the corresponding stochastic ordinary differential equations, via employing Ito´s formula under integral operator instead of directly applying Ito´s formula to Lyapunov functions in the case of stochastic ordinary differential equations, to aim at establishing the theory of dissipativity for Ito stochastic reaction diffusion systems. Some sufficient conditions for dissipativity and uniform dissipativity in mean square are given and this paper ends up with an example illustrating the obtained results.
  • Keywords
    Lyapunov methods; differential equations; stochastic processes; stochastic systems; Lyapunov function; integral operator; mean square dissipativity; spatial variable; stochastic functional differential equation; stochastic ordinary differential equation; stochastic reaction diffusion equation; stochastic reaction diffusion system; Differential equations; Indium tin oxide; Integral equations; Lyapunov method; Navier-Stokes equations; Partial differential equations; Stability; Stochastic processes; Stochastic resonance; Stochastic systems; Dissipativity; In mean square; Ito differential formula; Lyapunov function; Stochastic reaction diffusion systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370594
  • Filename
    4370594