Non-linear least squares estimation via network gossiping

Xiao Li; Anna Scaglione

doi:10.1109/ACSSC.2012.6489279

Non-linear least squares estimation via network gossiping

Xiao Li, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Pages	1508-1512
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2012.6489279
State	Published - Dec 1 2012
Externally published	Yes
Event	46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 - Pacific Grove, CA, United States Duration: Nov 4 2012 → Nov 7 2012

Publication series

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

Other

Other	46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Country/Territory	United States
City	Pacific Grove, CA
Period	11/4/12 → 11/7/12

Keywords

convergence
gossiping
least squares estimation

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2012.6489279

Cite this

Non-linear least squares estimation via network gossiping. / Li, Xiao; Scaglione, Anna.
Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012. 2012. p. 1508-1512 6489279 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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., 6489279, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 1508-1512, 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012, Pacific Grove, CA, United States, 11/4/12. https://doi.org/10.1109/ACSSC.2012.6489279

@inproceedings{56853d13c15d431b9e810d05a2a8a90b,

title = "Non-linear least squares estimation via network gossiping",

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.",

keywords = "convergence, gossiping, least squares estimation",

author = "Xiao Li and Anna Scaglione",

year = "2012",

month = dec,

day = "1",

doi = "10.1109/ACSSC.2012.6489279",

language = "English (US)",

isbn = "9781467350518",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

pages = "1508--1512",

booktitle = "Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012",

note = "46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 ; Conference date: 04-11-2012 Through 07-11-2012",

}

TY - GEN

T1 - Non-linear least squares estimation via network gossiping

AU - Li, Xiao

AU - Scaglione, Anna

PY - 2012/12/1

Y1 - 2012/12/1

N2 - 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.

AB - 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.

KW - convergence

KW - gossiping

KW - least squares estimation

UR - http://www.scopus.com/inward/record.url?scp=84876216097&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84876216097&partnerID=8YFLogxK

U2 - 10.1109/ACSSC.2012.6489279

DO - 10.1109/ACSSC.2012.6489279

M3 - Conference contribution

AN - SCOPUS:84876216097

SN - 9781467350518

T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers

SP - 1508

EP - 1512

BT - Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012

T2 - 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012

Y2 - 4 November 2012 through 7 November 2012

ER -

Non-linear least squares estimation via network gossiping

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this