A bound on the shannon capacity via a linear programming variation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We prove an upper bound on the Shannon capacity of a graph via a linear programming variation. We also show that our bound can be better than Lovász theta number and Haemers minimum rank bound.

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Information Theory, ISIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1063-1066
Number of pages4
ISBN (Electronic)9781509040964
DOIs
StatePublished - 9 Aug 2017
Event2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany
Duration: 25 Jun 201730 Jun 2017

Publication series

NameIEEE International Symposium on Information Theory - Proceedings

Conference

Conference2017 IEEE International Symposium on Information Theory, ISIT 2017
Country/TerritoryGermany
CityAachen
Period25/06/1730/06/17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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