Convergence rate of the modified DeGroot-Friedkin model with doubly stochastic relative interaction matrices
2016 (English)In: Proceedings of the American Control Conference, American Automatic Control Council (AACC) , 2016, 1054-1059 p.Conference paper (Refereed)
In a recent paper , a modified DeGroot-Friedkin model was proposed to study the evolution of the social-confidence levels of individuals in a reflected appraisal mechanism in which a network of n individuals consecutively discuss a sequence of issues. The individuals update their self-confidence levels on one issue in finite time steps, via communicating with their neighbors, instead of waiting until the discussion on the previous issue reaches a consensus, while the neighbor relationships are described by a static relative interaction matrix. This paper studies the same modified DeGroot-Friedkin model, but with time-varying interactions which are characterized by a sequence of doubly stochastic matrices. It is shown that, under appropriate assumptions, the n individuals' self-confidence levels will all converge to 1/n exponentially fast. An explicit expression of the convergence rate is provided.
Place, publisher, year, edition, pages
American Automatic Control Council (AACC) , 2016. 1054-1059 p.
Communication Studies Control Engineering
IdentifiersURN: urn:nbn:se:kth:diva-202178DOI: 10.1109/ACC.2016.7525054ScopusID: 2-s2.0-84992065827ISBN: 9781467386821 OAI: oai:DiVA.org:kth-202178DiVA: diva2:1079170
2016 American Control Conference, ACC 2016, 6 July 2016 through 8 July 2016
QC 201703072017-03-072017-03-072017-03-07Bibliographically approved