• DocumentCode
    3641653
  • Title

    Forward smoothing and online expectation-maximisation in Gaussian linear state-space models

  • Author

    Sinan Yıldırım;A. Taylan Cemgil

  • Author_Institution
    Statistical Laboratory, Cambridge Ü
  • fYear
    2011
  • fDate
    4/1/2011 12:00:00 AM
  • Firstpage
    530
  • Lastpage
    533
  • Abstract
    In this work, we studied forward-only smoothing recursion in Gaussian linear state-space (GLSS) models. We exploited a stochastic approximation of this recursion to develop an online version of the expectation-maximisation (EM) algorithm for GLSS models. We compared the performance of online EM with the conventional EM and demonstrated the advantages of its use in case of long data sequences.
  • Keywords
    "Markov processes","Hidden Markov models","Signal processing","Conferences","Signal processing algorithms","Smoothing methods","Art"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on
  • ISSN
    2165-0608
  • Print_ISBN
    978-1-4577-0462-8
  • Type

    conf

  • DOI
    10.1109/SIU.2011.5929704
  • Filename
    5929704
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3641653