Convergence analysis of consensus-based distributed clustering

Pedro A. Forero, Alfonso Cano, Georgios B Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper deals with clustering of spatially distributed data using wireless sensor networks. A distributed low-complexity clustering algorithm is developed that requires one-hop communications among neighboring nodes only, without local data exchanges. The algorithm alternates iterations over the variables of a consensus-based version of the global clustering problem. Using stability theory for time-varying and time-invariant systems, the distributed clustering algorithm is shown to be bounded-input bounded-output stable with an output arbitrarily close to a fixed point of the algorithm. For distributed hard K-means clustering, convergence to a local minimum of the centralized problem is guaranteed. Numerical examples confirm the merits of the algorithm and its stability analysis.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages1890-1893
Number of pages4
DOIs
StatePublished - Nov 8 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period3/14/103/19/10

Keywords

  • Clustering methods
  • Distributed algorithms
  • Stability
  • Unsupervised learning

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  • Cite this

    Forero, P. A., Cano, A., & Giannakis, G. B. (2010). Convergence analysis of consensus-based distributed clustering. In 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings (pp. 1890-1893). [5495344] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2010.5495344