• DocumentCode
    2413239
  • Title

    Entropy analysis of generalized stochastic Petri net s-transitions

  • Author

    Watson, James F., III ; Desrochers, Alan A.

  • Author_Institution
    Dept. of Electr.-Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
  • fYear
    1992
  • fDate
    1992
  • Firstpage
    1204
  • Abstract
    A density function can be formulated with the maximum entropy method (MEM) that achieves entropy while meeting various constraints. The following three constraints are considered in the present work: a specified mean a specified variance, and knowledge that the density is one-sided (i.e., positive domain). A 1D gradient search (i.e., a line search) for obtaining the maximum entropy density is presented. Entropy and performance analysis results on a manufacturing system example are presented to compare the s-transition and maximum entropy density functions (MEDFs). The similarity between MEDF transitions and s-transitions is shown
  • Keywords
    Petri nets; discrete systems; entropy; stochastic processes; 1D gradient search; density function; generalized stochastic Petri net s-transitions; line search; manufacturing system; maximum entropy method; positive domain; specified mean; specified variance; Density functional theory; Entropy; Intelligent robots; Kernel; Manufacturing systems; Mathematical model; Orbital robotics; Performance analysis; Petri nets; Space exploration; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
  • Conference_Location
    Tucson, AZ
  • Print_ISBN
    0-7803-0872-7
  • Type

    conf

  • DOI
    10.1109/CDC.1992.371526
  • Filename
    371526