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Extension of some results for channel capacity using a generalized information measure

dc.contributor.authorTeboulle, Marcen_US
dc.contributor.authorBen-Tal, Aharonen_US
dc.date.accessioned2006-09-11T19:45:32Z
dc.date.available2006-09-11T19:45:32Z
dc.date.issued1988-01en_US
dc.identifier.citationBen-Tal, Aharon; Teboulle, Marc; (1988). "Extension of some results for channel capacity using a generalized information measure." Applied Mathematics & Optimization 17(1): 121-132. <http://hdl.handle.net/2027.42/48091>en_US
dc.identifier.issn0095-4616en_US
dc.identifier.issn1432-0606en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/48091
dc.description.abstractA new formulation for the channel capacity problem is derived by using the duality theory of convex programming. The simple nature of this dual representation is suitable for computational purposes. The results are derived in a unified way by formulating the channel capacity problem as a special case of a general class of concave programming problems involving a generalized information measure recently introduced by Burbea and Rao [10].en_US
dc.format.extent608095 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlagen_US
dc.subject.otherMathematical and Computational Physicsen_US
dc.subject.otherNumerical and Computational Methodsen_US
dc.subject.otherMathematicsen_US
dc.subject.otherSystems Theory, Controlen_US
dc.subject.otherMathematical Methods in Physicsen_US
dc.subject.otherOptimizationen_US
dc.subject.otherCalculus of Variations and Optimal Controlen_US
dc.titleExtension of some results for channel capacity using a generalized information measureen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumTechnion, Israel Institute of Technology, Haifa, Israel; Department of Industrial and Operations Engineering, University of Michigan, 48109, Ann Arbor, MI, USAen_US
dc.contributor.affiliationotherDepartment of Mathematics, Statistics and Computing Science, Dalhousie University, B3H 3J5, Halifax, Nova Scotia, Canadaen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/48091/1/245_2005_Article_BF01448363.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF01448363en_US
dc.identifier.sourceApplied Mathematics & Optimizationen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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