On the design of dynamic associative neural memories

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dc.citation.epage492en_US
dc.citation.issueNumber3en_US
dc.citation.spage489en_US
dc.citation.volumeNumber5en_US
dc.contributor.authorSavran, M. E.en_US
dc.contributor.authorMorgül, Ö.en_US
dc.date.accessioned2016-02-08T10:53:27Z
dc.date.available2016-02-08T10:53:27Z
dc.date.issued1994en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractWe consider the design problem for a class of discrete-time and continuous-time neural networks. We obtain a characterization of all connection weights that store a given set of vectors into the network; that is, each given vector becomes an equilibrium point of the network. We also give sufficient conditions that guarantee the asymptotic stability of these equilibrium points.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:53:27Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1994en
dc.identifier.doi10.1109/72.286920en_US
dc.identifier.issn1045-9227
dc.identifier.urihttp://hdl.handle.net/11693/25993
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/72.286920en_US
dc.source.titleIEEE Transactions on Neural Networksen_US
dc.subjectConvergence of numerical methodsen_US
dc.subjectMathematical modelsen_US
dc.subjectNeural networksen_US
dc.subjectSystem stabilityen_US
dc.subjectSystems analysisen_US
dc.subjectVectorsen_US
dc.subjectAsymptotic stabilityen_US
dc.subjectContinuous time neural networksen_US
dc.subjectDiscrete time neural networksen_US
dc.subjectDynamic associative neural memoriesen_US
dc.subjectEquilibrium pointsen_US
dc.subjectAssociative storageen_US
dc.titleOn the design of dynamic associative neural memoriesen_US
dc.typeArticleen_US

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