Scaling laws for consensus protocols subject to noise
classification
🧮 math.OC
cs.DCcs.SYeess.SYmath.PR
keywords
consensusnoiseprotocolsgraphtermsunderlyingadditivechain
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We study the performance of discrete-time consensus protocols in the presence of additive noise. When the consensus dynamic corresponds to a reversible Markov chain, we give an exact expression for a weighted version of steady-state disagreement in terms of the stationary distribution and hitting times in an underlying graph. We then show how this result can be used to characterize the noise robustness of a class of protocols for formation control in terms of the Kemeny constant of an underlying graph.
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