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Cited by 218

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Fast linear iterations for distributed averaging

Lin Xiao, Boyd, S.·2004·42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475)
DOI 10.1109/cdc.2003.1272421
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Abstract

We consider the problem of finding a linear iteration that yields distributed averaging consensus over a network, i.e., that asymptotically computes the average of some initial values given at the nodes. When the iteration is assumed symmetric, the problem of finding the fastest converging linear iteration can be cast as a semidefinite program, and therefore efficiently and globally solved. These optimal linear iterations are often substantially faster than several simple heuristics that are based on the Laplacian matrix of the associated graph.

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Metadata

Authors
Xiao, L., & Boyd, S.
Venue
42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475)
Publisher
IEEE
Published
2004-06-21
Pages
4997-5002
DOI
10.1109/cdc.2003.1272421
OpenAlex
W2169593613
Cited by
218
References
4
FWCI
2.06
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fast linear iterations for distributed averaging. https://app.cochat.ai/papers/10.1109/cdc.2003.1272421
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Xiao, L., & Boyd, S. (2004). Fast linear iterations for distributed averaging. 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475). https://doi.org/10.1109/cdc.2003.1272421

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.