• DocumentCode
    29561
  • Title

    Modal Trajectory Estimation Using Maximum Gaussian Mixture

  • Author

    Monin, A.

  • Author_Institution
    LAAS, Toulouse, France
  • Volume
    58
  • Issue
    3
  • fYear
    2013
  • fDate
    Mar-13
  • Firstpage
    763
  • Lastpage
    768
  • Abstract
    This technical note deals with the estimation of the whole trajectory of a stochastic dynamic system with highest probability, conditionally upon the past observation process, using a maximum Gaussian mixture. We first recall the Gaussian sum technique applied to minimum variance filtering. It is then shown that the same concept of Gaussian mixture can be applied in that context, provided we replace the Sum operator by the Max operator.
  • Keywords
    Gaussian processes; estimation theory; filtering theory; mathematical operators; stochastic processes; Gaussian sum technique; Max operator; Sum operator; maximum Gaussian mixture; minimum variance filltering; modal trajectory estimation; past observation process; stochastic dynamic system whole trajectory; Approximation algorithms; Approximation methods; Bayesian methods; Kalman filters; Noise; Probability density function; Trajectory; Filtering; Gaussian mixture; Gaussian sum; smoothing;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2012.2211439
  • Filename
    6257427