Fault tolerance is an important issue in network design because sensor networks must work in a dynamic, uncertain situation. In this paper, using Dempster-Shafer theory of evidence, we propose several new fault-tolerant interval integration functions, which give interval estimate fusion outputs and the corresponding belief levels, depending on prior information and practical requirements. Not only do these functions have a smaller output interval than that given by Marzullo function, but they also satisfy the local Lipschitz condition, which makes our algorithm locally stable.


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    Titel :

    Fault-tolerant interval estimation fusion by Dempster-Shafer theory


    Beteiligte:
    Baohua Li, (Autor:in) / Yunmin Zhu, (Autor:in) / Rong Li, X. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    492762 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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