• DocumentCode
    3482747
  • Title

    Trellis-based search of the maximum a posteriori sequence using particle filtering

  • Author

    Bertozzi, Tanya ; Le Ruyet, Didier ; Rigal, Gilles ; Vu-Thien, Han

  • Author_Institution
    DIGINEXT, Aix En Provence, France
  • Volume
    6
  • fYear
    2003
  • fDate
    6-10 April 2003
  • Abstract
    For a given computational complexity, the Viterbi algorithm applied on the discrete representation of the state space provided by a standard particle filtering, outperforms the particle filtering. However, the computational complexity of the Viterbi algorithm is still high. We propose to use the M and T algorithms in order to reduce the computational complexity of the Viterbi algorithm and we show that these algorithms enable a reduction of the number of particles by up to 20%, practically without loss of performance with respect to the Viterbi algorithm.
  • Keywords
    Monte Carlo methods; computational complexity; discrete systems; filtering theory; maximum likelihood estimation; nonlinear filters; search problems; state estimation; state-space methods; Viterbi algorithm; computational complexity; maximum a posteriori sequence; nonlinear filtering; particle filtering; sequential Monte Carlo methods; state estimation; trellis-based search; Computational complexity; Data analysis; Filtering; Mathematical model; Sensor phenomena and characterization; Sensor systems; State estimation; State-space methods; Viterbi algorithm; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7663-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2003.1201776
  • Filename
    1201776