Non-linear least squares estimation via network gossiping

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

1 Scopus citations

Abstract

Various estimation problems can be formulated as non-linear least squares (NLLS) problems, which can be solved using the Gauss-Newton algorithm. In this paper, we use gossiping to implement the Gauss-Newton algorithm in a fully distributed fashion, and show the convergence of this Gossip-based Gauss-Newton (GGN) algorithm. As an example, we show by simulations that the GGN algorithm is effective and robust in solving power system state estimation, and that the Mean Square Error (MSE) performance remains comparable to the centralized scheme and degrades gracefully even with random link/node failures.

Original languageEnglish (US)
Title of host publicationConference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Pages1508-1512
Number of pages5
DOIs
StatePublished - Dec 1 2012
Externally publishedYes
Event46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 - Pacific Grove, CA, United States
Duration: Nov 4 2012Nov 7 2012

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
CountryUnited States
CityPacific Grove, CA
Period11/4/1211/7/12

Keywords

  • convergence
  • gossiping
  • least squares estimation

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Li, X., & Scaglione, A. (2012). Non-linear least squares estimation via network gossiping. In Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 (pp. 1508-1512). [6489279] (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2012.6489279