Convergence Rate of the Modified DeGroot-Friedkin Model with Doubly Stochastic Relative Interaction Matrices
2016 (English)In: 2016 AMERICAN CONTROL CONFERENCE (ACC), IEEE conference proceedings, 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
IEEE conference proceedings, 2016. 1054-1059 p.
Proceedings of the American Control Conference, ISSN 0743-1619
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-204145DOI: 10.1109/ACC.2016.7525054ISI: 000388376101016ScopusID: 2-s2.0-84992065827ISBN: 978-1-4673-8682-1 OAI: oai:DiVA.org:kth-204145DiVA: diva2:1085096
American Control Conference (ACC), JUL 06-08, 2016, Boston, MA
QC 201703282017-03-282017-03-282017-03-28Bibliographically approved