Convergence and applications of a gossip-based Gauss-Newton algorithm

Xiao Li, Anna Scaglione

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

The Gauss-Newton algorithm is a popular and efficient centralized method for solving non-linear least squares (NLLS) problems. In this paper, a multi-agent distributed version of this algorithm is proposed to solve general NLLS problems in a network, named Gossip-based Gauss-Newton (GGN) algorithm. Furthermore, we analyze and present sufficient conditions for its convergence and show numerically that the GGN algorithm achieves performance comparable to the centralized algorithm, with graceful degradation in case of network failures. More importantly, the GGN algorithm provides significant performance gains compared to other distributed first order methods.

Original languageEnglish (US)
Article number6574279
Pages (from-to)5231-5246
Number of pages16
JournalIEEE Transactions on Signal Processing
Volume61
Issue number21
DOIs
StatePublished - 2013
Externally publishedYes

Keywords

  • Gauss-Newton
  • convergence
  • distributed
  • gossip

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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