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dc.contributor.authorMatei, Ion
dc.contributor.authorSomarakis, Christoforos
dc.contributor.authorBaras, John
dc.date.accessioned2012-02-20T16:38:35Z
dc.date.available2012-02-20T16:38:35Z
dc.date.issued2012-02-20
dc.identifier.urihttp://hdl.handle.net/1903/12413
dc.description.abstractA consensus problem consists of a group of dynamic agents who seek to agree upon certain quantities of interest. This problem can be generalized in the context of convex metric spaces that extend the standard notion of convexity. In this paper we introduce and analyze a randomized gossip algorithm for solving the generalized consensus problem on convex metric spaces. We study the convergence properties of the algorithm using stochastic differential equations theory. We show that the dynamics of the distances between the states of the agents can be upper bounded by the dynamics of a stochastic differential equation driven by Poisson counters. In addition, we introduce instances of the generalized consensus algorithm for several examples of convex metric spaces together with numerical simulations.en_US
dc.description.sponsorshipThis material is based in part upon work supported by the NIST-ARRA Measurement Science and Engineering Fellowship Program award 70NANB10H026, through the University of Maryland, and in part upon work supported by the Army Research Office award number W911NF-08-1-0238 to Ohio State University.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesTR_2012-02
dc.subjectconvex metric spacesen_US
dc.subjectrandom processesen_US
dc.subjectgossip algorithmen_US
dc.subjectconsensusen_US
dc.titleA randomized gossip consensus algorithm on convex metric spacesen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtInstitute for Systems Researchen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us


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