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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributorWayamba University of Sri Lanka
dc.contributorUniversity of Peradeniya
dc.contributor.authorJayasinghe, Jeevani
dc.contributor.authorAnguera Pros, Jaume
dc.contributor.authorUduwawala, Disala
dc.date.accessioned2020-05-08T14:20:48Z
dc.date.accessioned2023-10-02T06:37:55Z
dc.date.available2020-05-08T14:20:48Z
dc.date.available2023-10-02T06:37:55Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3371
dc.description.abstractGenetic algorithm (GA) is a popular optimization technique used in the design of performance improved microstrip patch antennas (MPAs). The fitness function plays a vital role in the successful application of GA in MPAs. This paper investigates the performance of several fitness functions for achieving bandwidth improved MPAs.eng
dc.format.extent6 p.cat
dc.language.isoengcat
dc.publisherScience Publishing Corporationcat
dc.relation.ispartofInternational Journal of Scientific World, 2015. Vol. 3, 1cat
dc.rightsAttribution 4.0 International
dc.rights© L'autor/a
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherTelefonia mòbilcat
dc.subject.otherComunicacions mòbils, Sistemes decat
dc.subject.otherAntenes (Electrònica)cat
dc.titleOn the behavior of several fitness functions for genetically optimized microstrip antennascat
dc.typeinfo:eu-repo/semantics/articlecat
dc.typeinfo:eu-repo/semantics/publishedVersioncat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat
dc.subject.udc621.3
dc.identifier.doihttp://doi.org/ 10.14419/ijsw.v3i1.4132cat


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/
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