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A CONTINUATION METHOD FOR LARGE-SIZED SENSOR NETWORK LOCALIZATION PROBLEMS

Title
A CONTINUATION METHOD FOR LARGE-SIZED SENSOR NETWORK LOCALIZATION PROBLEMS
Authors
Kim, SunyoungKojima, Masakazu
Ewha Authors
김선영
SCOPUS Author ID
김선영scopus
Issue Date
2013
Journal Title
PACIFIC JOURNAL OF OPTIMIZATION
ISSN
1348-9151JCR Link
Citation
vol. 9, no. 1, pp. 117 - 136
Keywords
sensor network localization problemscontinuation methodsa first-order methodMatlab software package
Publisher
YOKOHAMA PUBL
Indexed
SCIE WOS
Abstract
The solution methods based on semidefinite programming (SDP) relaxations for sensor network localization (SNL) problems can not handle very large-sized SNL problems. We present a continuation method using the gradient descent method to efficiently solve large-sized SNL problems. We first formulate the problem as an unconstrained optimization problem and then apply the continuation on the distance information with the continuation parameter. We show numerically that the continuation method provides an approximate solution efficiently with comparable accuracy to that of SFSDP, a Matlab software package, which showed better performance than other SDP-based methods for solving various types of the problems. Numerical results are presented to illustrate the performance of the proposed method in comparison with SFSDP.
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자연과학대학 > 수학전공 > Journal papers
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