• DocumentCode
    818787
  • Title

    New finite-dimensional filters and smoothers for noisily observed Markov chains

  • Author

    Elliott, Robert J.

  • Author_Institution
    Dept. of Stat. & Appl. Probability, Alberta Univ., Edmonton, Alta., Canada
  • Volume
    39
  • Issue
    1
  • fYear
    1993
  • fDate
    1/1/1993 12:00:00 AM
  • Firstpage
    265
  • Lastpage
    271
  • Abstract
    New finite-dimensional filters and smoothers that are related to the Wonham filter of a noisily observed Markov chain are obtained. In particular, finite-dimensional, recursive filters and smoothers are given for the number of jumps from state i to state j, for the occupation time of state i, and for a stochastic integral related to the drift in the observations. These filters allow easy application of the EM algorithm for the estimation of the parameters of the Markov chain and observation process
  • Keywords
    Markov processes; filtering and prediction theory; parameter estimation; EM algorithm; Wonham filter; expectation-maximisation algorithm; finite-dimensional filters; noisily observed Markov chains; observation process; parameter estimation; recursive filters; smoothers; stochastic integral; Equations; Filters; Parameter estimation; Random variables; Signal processing; Signal processing algorithms; State estimation; State-space methods; Statistics; Stochastic processes;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.179372
  • Filename
    179372
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=818787