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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    Title :

    Fault-tolerant interval estimation fusion by Dempster-Shafer theory


    Contributors:
    Baohua Li, (author) / Yunmin Zhu, (author) / Rong Li, X. (author)


    Publication date :

    2002-01-01


    Size :

    492762 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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