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dc.contributor.advisorSezer, Erol
dc.contributor.authorAkar, Mehmet
dc.date.accessioned2016-01-08T20:13:37Z
dc.date.available2016-01-08T20:13:37Z
dc.date.issued1996
dc.identifier.urihttp://hdl.handle.net/11693/17812
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1996.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 1996.en_US
dc.descriptionIncludes bibliographical references leaves 66-68.en_US
dc.description.abstractThis thesis is concerned with the anaiysis and synthesis of neurai networks to be used as associative memories. First considering a discrete-time neurai network modei which uses a quantizer-type muitiievei activation function, a way of seiecting the connection weights is proposed. In addition to this, the idea of overiapping decompositions, which is extensiveiy used in the soiution of iarge-scaie probiems, is appiied to discrete-time neurai networks with binary neurons. 'I’lie necesscuy toois for expansions and contractions are derived, and algorithms for decomposition of a set equiiibria into smaiier dimensionai equiiibria sets and for designing neurai networks for these smaiier ciimensionai equiiibria sets are given. The concept is iiiustrated with various exarnpies.en_US
dc.description.statementofresponsibilityAkar, Mehmeten_US
dc.format.extentix, 68 leavesen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectHopfieid neurai networken_US
dc.subjectcissociative memory designen_US
dc.subjectmuitiievei activation functionen_US
dc.subjectoveriapping decompositionen_US
dc.subject.lccQA76.87 .A33 1996en_US
dc.subject.lcshNeural networks (Computer science).en_US
dc.subject.lcshAssociative storage.en_US
dc.subject.lcshMachine theory.en_US
dc.titleVariations in associative memory designen_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


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