Distributed Matrix Scaling and Application to Average Consensus in Directed Graphs.

IEEE Trans. Automat. Contr., no. 3 (2013): 667-681

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We propose a class of distributed iterative algorithms that enable the asymptotic scaling of a primitive column stochastic matrix, with a given sparsity structure, to a doubly stochastic form. We also demonstrate the application of these algorithms to the average consensus problem in networked multi-component systems. More specifically, w...更多

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