Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/19642
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dc.contributor.authorLim, Tee Hong.en_US
dc.date.accessioned2009-12-14T06:19:28Z-
dc.date.available2009-12-14T06:19:28Z-
dc.date.copyright1996en_US
dc.date.issued1996-
dc.identifier.urihttp://hdl.handle.net/10356/19642-
dc.description.abstractThis is a study of the dynamics of neural network as formulated by Hopfield in 1982. Various update algorithms are analysed and these include the synchronous update, the asynchronous update, the best neighbour update, the gradient update and the modified gradient update. A study was also carried out on the use of neural networks in pattern domains like error correcting codes, image scene recognition and Boolean logic problems.en_US
dc.format.extent82 p.-
dc.language.isoen-
dc.rightsNANYANG TECHNOLOGICAL UNIVERSITYen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems-
dc.titleConvergence properties of 2-state neural networks with associate memoryen_US
dc.typeThesisen_US
dc.contributor.supervisorArichandranen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Communication and Network Systems)en_US
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
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