• DocumentCode
    2621252
  • Title

    Kalman like filtering and smoothing for reciprocal sequences

  • Author

    Baccarelli, E. ; Cusani, R. ; Blasio, G. Di

  • Author_Institution
    INFOCOM Dept., Rome Univ., Italy
  • fYear
    1994
  • fDate
    27 Jun-1 Jul 1994
  • Firstpage
    123
  • Abstract
    The MMSE filtering problem of reciprocal Gaussian sequences in additive white Gaussian noise is solved in a recursive and causal form. The solution, based on the innovations method, is expressed in terms of a set of recursive equations formally similar to those of the well-known Kalman filter; it gives as by-product the solution of the MMSE smoothing problems (fixed-point, fixed-interval, fixed-lag). The performance of the proposed estimators is also given by recursive expressions
  • Keywords
    Gaussian noise; Kalman filters; Markov processes; estimation theory; physics fundamentals; recursive filters; sequences; smoothing methods; white noise; Gaussian sequences; Kalman like filtering; MMSE filtering problem; additive white Gaussian noise; causal form; estimators; innovations method; performance; reciprocal sequences; recursive expressions; smoothing; AWGN; Equations; Filtering; Gaussian processes; Kalman filters; Markov processes; Recursive estimation; Smoothing methods; Statistics; Technological innovation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
  • Conference_Location
    Trondheim
  • Print_ISBN
    0-7803-2015-8
  • Type

    conf

  • DOI
    10.1109/ISIT.1994.394848
  • Filename
    394848