• DocumentCode
    2750766
  • Title

    Risk-sensitive identification of ARMA processes

  • Author

    Gerencser, L. ; Michaletzky, Gyöorgy ; Vago, Zsuzsanna

  • Author_Institution
    Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
  • Volume
    1
  • fYear
    1998
  • fDate
    1998
  • Firstpage
    215
  • Abstract
    A new definition of risk-sensitive recursive identification is given, which is applicable to ARMA-system and even to general linear stochastic systems. The new identification criterion is defined in terms of a suitably transformed estimation-error process, and an exponential cost function. Applying stochastic realization theory and the bounded real lemma we derive an alternative expression for the LEQG cost function. A key design parameter is the weight matrix that is used in the recursive estimation. Its optimal value is found in explicit form. These results generalize the results of Stoorvogel and van Schuppen (1995) for risk-sensitive identification of AR-processes
  • Keywords
    autoregressive moving average processes; matrix algebra; realisation theory; recursive estimation; stochastic systems; ARMA processes; LEQG cost function; bounded real lemma; exponential cost function; linear stochastic systems; recursive estimation; risk-sensitive recursive identification; stochastic realization theory; transformed estimation-error process; weight matrix; Costs; Lagrangian functions; Riccati equations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-4394-8
  • Type

    conf

  • DOI
    10.1109/CDC.1998.760671
  • Filename
    760671