Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/40777
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dc.coverage.spatialTowards SOPC architectures for a Complete hardware evolution based Genetic algorithmen_US
dc.date.accessioned2015-05-09T08:36:38Z-
dc.date.available2015-05-09T08:36:38Z-
dc.date.issued2015-05-09-
dc.identifier.urihttp://hdl.handle.net/10603/40777-
dc.description.abstractA Genetic Algorithm GA is a computer based search optimization newlinetechnique that uses the Darwinian Theory of Evolution as a model for newlinefinding exact and approximate solutions GAs belong to a large family of newlineheuristic algorithms called Evolutionary algorithms EA which are being newlineincreasingly utilized for solving complex optimization and search problems newlineThey are basically implemented in either software or in hardware newlineTraditionally GAs are implemented using only software Change being an newlineimportant attribute of GA is handled very easily in software and hardware newlineimplementation was impossible until the advent of reconfigurable hardware newlinetechnology However the large computational time consumed by a GA newlineimplemented in software makes it unsuitable for real time applications newlineToday with the advancements happening in the reconfigurable hardware newlineTechnology this hurdle is overcome thereby shifting the implementation to newlineHardware which drastically speeds up the time factor thus presenting a scope newlinefor real time applications newlineGAs are used for many applications like designing optimization newlinesearch and organization classification and many more Hardware newlinearchitectures in the form of System on Programmable Chip SoPC which are newlinecustomizable for specific GA applications are proposed designed and newlinepresented in this thesis These architectures are based on Complete Hardware newlineEvolution CHE and so the different operations of the GA newline newlineen_US
dc.format.extentxx, 140p.en_US
dc.languageEnglishen_US
dc.relationp126-139.en_US
dc.rightsuniversityen_US
dc.titleTowards SOPC architectures for a Complete hardware evolution based Genetic algorithmen_US
dc.title.alternativeen_US
dc.creator.researcherAlagala swarnalathaen_US
dc.subject.keywordComplete Hardware Evolutionen_US
dc.subject.keywordDarwinian Theory of Evolutionen_US
dc.subject.keywordEvolutionary algorithmsen_US
dc.subject.keywordGenetic Algorithmen_US
dc.subject.keywordSystem on Programmable Chipen_US
dc.description.notereference p126-139.en_US
dc.contributor.guideShanthi A Pen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/06/2014en_US
dc.date.awarded30/06/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificate.pdf1.06 MBAdobe PDFView/Open
03_abstract.pdf11.59 kBAdobe PDFView/Open
04_acknowledgement.pdf6.02 kBAdobe PDFView/Open
05_content.pdf20.89 kBAdobe PDFView/Open
06_chapter1.pdf51.8 kBAdobe PDFView/Open
07_chapter2.pdf73.07 kBAdobe PDFView/Open
08_chapter3.pdf93.01 kBAdobe PDFView/Open
09_chapter4.pdf962.11 kBAdobe PDFView/Open
10_chapter5.pdf448.58 kBAdobe PDFView/Open
11_chapter6.pdf87.67 kBAdobe PDFView/Open
12_chapter7.pdf15.95 kBAdobe PDFView/Open
13_reference.pdf42.18 kBAdobe PDFView/Open
14_publication.pdf5.49 kBAdobe PDFView/Open


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