Products of stochastic matrices: Large deviation rate for Markov chain temporal dependencies

  • Dragana Bajovic
  • , Joao Xavier
  • , Bruno Sinopoli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We find the large deviation rate I for convergence in probability of the product Wk C⋯W1W0 of temporally dependent random stochastic matrices. As the model for temporal dependencies, we adopt the Markov chain whose set of states is the set of all possible graphs that support the matrices Wk. Such model includes, for example, 1) token-based protocols, where a token is passed among nodes to determine the order of processing; and 2) temporally dependent link failures, where the temporal dependence is modeled by a Markov chain. We characterize the rate I as a function of the Markov chain transition probability matrix P. Examples further reveal how the temporal correlations (dependencies) affect the rate of convergence in probability I.

Original languageEnglish
Title of host publication2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012
Pages724-729
Number of pages6
DOIs
StatePublished - 2012
Event2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012 - Monticello, IL, United States
Duration: Oct 1 2012Oct 5 2012

Publication series

Name2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012

Conference

Conference2012 50th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2012
Country/TerritoryUnited States
CityMonticello, IL
Period10/1/1210/5/12

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