A distance metric between directed weighted graphs

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

Abstract

Directed weighted graphs are increasingly used to model complex systems and interactions, such as networks of interconnected physical or biological subsystems. The analysis of these graphs often requires some form of dissimilarity, or distance measure to compare graphs. In this paper, we extend connectivity-based dissimilarity measures previously used to compare unweighted undirected graphs of the same dimensions to: (1) directed weighted graphs of the same dimensions and (2) directed weighted graphs of different dimensions. To our knowledge, this is the first approach proposed for comparing two graphs containing different numbers of nodes. We derive the conditions under which this dissimilarity measure is a pseudo-metric. This derivation provides new insights on our algorithms (previously proposed) for the graph aggregation optimization problem.

Original languageEnglish (US)
Title of host publication2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6359-6364
Number of pages6
ISBN (Print)9781467357173
DOIs
StatePublished - 2013
Event52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
Duration: Dec 10 2013Dec 13 2013

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other52nd IEEE Conference on Decision and Control, CDC 2013
Country/TerritoryItaly
CityFlorence
Period12/10/1312/13/13

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint

Dive into the research topics of 'A distance metric between directed weighted graphs'. Together they form a unique fingerprint.

Cite this