• DocumentCode
    2750493
  • Title

    A new Bayesian estimation approach for continuous-time systems

  • Author

    Hamidi-Hashemi, H.

  • Author_Institution
    Dept. of Electr. Eng., California State Univ., Fullerton, CA
  • Volume
    2
  • fYear
    1994
  • fDate
    3-5 Aug 1994
  • Firstpage
    987
  • Abstract
    In this paper, a new Bayesian estimation method is introduced. This new method provides estimation for the state variable through a locally correlated process. It utilizes both range and smoothing parameters. Therefore, it has the flexibility of the nonparametric approach as well as the adaptability of the Bayesian estimation. In addition, its convergence and some of its properties are discussed
  • Keywords
    Bayes methods; continuous time filters; continuous time systems; convergence; linear network analysis; state estimation; Bayesian estimation method; active filters; continuous-time systems; convergence; state variable estimation; Bandwidth; Bayesian methods; Convergence; Covariance matrix; Equations; Kernel; Polynomials; Smoothing methods; Spline; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
  • Conference_Location
    Lafayette, LA
  • Print_ISBN
    0-7803-2428-5
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1994.518977
  • Filename
    518977