A saturated linear dynamical network for approximating maximum clique

dc.citation.epage685en_US
dc.citation.issueNumber6en_US
dc.citation.spage677en_US
dc.citation.volumeNumber46en_US
dc.contributor.authorPekergin, F.en_US
dc.contributor.authorMorgül, Ö.en_US
dc.contributor.authorGüzeliş, C.en_US
dc.date.accessioned2016-02-08T10:40:05Z
dc.date.available2016-02-08T10:40:05Z
dc.date.issued1999-06en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractWe use a saturated linear gradient dynamical network for finding an approximate solution to the maximum clique problem. We show that for almost all initial conditions, any solution of the network defined on a closed hypercube reaches one of the vertices of the hypercube, and any such vertex corresponds to a maximal clique. We examine the performance of the method on a set of random graphs and compare the results with those of some existing methods. The proposed model presents a simple continuous, yet powerful, solution in approximating maximum clique, which may outperform many relatively complex methods, e.g., Hopfield-type neural network based methods and conventional heuristics.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:40:05Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1999en
dc.identifier.doi10.1109/81.768824en_US
dc.identifier.issn1057-7122
dc.identifier.urihttp://hdl.handle.net/11693/25155
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/81.768824en_US
dc.source.titleIEEE Transactions on Circuits and Systems I : Fundamental Theory and Applicationsen_US
dc.subjectCombinatorial optimizationen_US
dc.subjectGradient systemsen_US
dc.subjectMax cliqueen_US
dc.subjectNeural networksen_US
dc.subjectApproximation theoryen_US
dc.subjectComputational complexityen_US
dc.subjectGraph theoryen_US
dc.subjectLinear programmingen_US
dc.subjectProblem solvingen_US
dc.subjectQuadratic programmingen_US
dc.subjectMaximum clique problemen_US
dc.subjectSaturated linear gradient dynamical networken_US
dc.subjectNeural networksen_US
dc.titleA saturated linear dynamical network for approximating maximum cliqueen_US
dc.typeArticleen_US

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