A suboptimal algorithm to fixed-interval and fixed-lag smoothing for Markovian switching systems is proposed. It infers a Gaussian mixture approximation of the smoothing pdf by combining the statistics produced by an IMM filter into an original backward recursive process. The number of filters and smoothers is equal to the constant number of hypotheses in the posterior mixture. A comparison, conducted on simulated case studies, shows that the investigated method performs significantly better than equivalent algorithms.


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    Titel :

    Low-Complexity IMM Smoothing for Jump Markov Nonlinear Systems


    Beteiligte:
    Lopez, Remy (Autor:in) / Danes, Patrick (Autor:in)


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    1142540 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch