• DocumentCode
    1191039
  • Title

    Estimation of Markov-modulated time-series via EM algorithm

  • Author

    Dey, Subhrakanti ; Krishnamurthy, Vikram ; Salmon-Legagneur, Thierry

  • Author_Institution
    Dept. of Syst. Eng., Australian Nat. Univ., Canberra, ACT, Australia
  • Volume
    1
  • Issue
    10
  • fYear
    1994
  • Firstpage
    153
  • Lastpage
    155
  • Abstract
    We consider the estimation of various Markov-modulated time series. We obtain maximum likelihood estimates of the time-series parameters including the Markov chain transition probabilities and the time-series coefficients using the expectation maximization (EM) algorithm. In addition, the recursive EM algorithm is used to obtain on-line parameter estimates. Simulation studies show that both algorithms yield satisfactory results.<>
  • Keywords
    Markov processes; maximum likelihood estimation; probability; signal processing; time series; EM algorithm; Markov chain transition probabilities; Markov-modulated time-series; expectation maximization algorithm; maximum likelihood estimates; on-line parameter estimates; recursive EM algorithm; simulation studies; time-series coefficients; time-series parameters; Adaptive systems; Australia; Econometrics; Image segmentation; Maximum likelihood estimation; Parameter estimation; Polynomials; Recursive estimation; Robustness; Signal processing algorithms;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/97.329841
  • Filename
    329841
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1191039