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Non-Asymptotic Analysis of an Optimal Algorithm for Network-Constrained Averaging With Noisy Links
IEEE Journal on Selected Topics in Signal Processing
The problem of network-constrained averaging is to compute the average of a set of values distributed throughout a graph G using an algorithm that can pass messages only along graph edges. We study this problem in the noisy setting, in which the communication along each link is modeled by an additive white Gaussian noise channel. We propose a two-phase decentralized algorithm, and we use stochastic approximation methods in conjunction with the spectral graph theory to provide concretedoi:10.1109/jstsp.2011.2122241 fatcat:2cl7v4wkafgghhd5iglhahswwq