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These algorithms perform a set-membership estimation, where only the maximal number of outliers is required to be known. Using these algorithms, estimates consist of sets of boxes whose union surely contains the correct location of the sensor, provided that the considered hypotheses are satisfied. This paper proposes as well a technique for evaluating the number of outliers to be robust to. In order to corroborate the efficiency of both algorithms, a comparison of their performances is performed in simulations using Matlab. <\/jats:p>","DOI":"10.1155\/2012\/303895","type":"journal-article","created":{"date-parts":[[2011,11,1]],"date-time":"2011-11-01T19:01:02Z","timestamp":1320174062000},"page":"303895","update-policy":"http:\/\/dx.doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Robust Interval-Based Localization Algorithms for Mobile Sensor Networks"],"prefix":"10.1177","volume":"8","author":[{"given":"Farah","family":"Mourad","sequence":"first","affiliation":[{"name":"Institut Charles Delaunay (ICD)\u2014LM2S (STMR UMR CNRS 6279), Universit\u00e9 de Technologie de Troyes, 12 rue Marie Curie, 10010 Troyes, France"}]},{"given":"Hichem","family":"Snoussi","sequence":"additional","affiliation":[{"name":"Institut Charles Delaunay (ICD)\u2014LM2S (STMR UMR CNRS 6279), Universit\u00e9 de Technologie de Troyes, 12 rue 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