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dc.contributor.authorCHANG, JYen_US
dc.contributor.authorWU, CCen_US
dc.date.accessioned2014-12-08T15:04:16Z-
dc.date.available2014-12-08T15:04:16Z-
dc.date.issued1993-11-25en_US
dc.identifier.issn0013-5194en_US
dc.identifier.urihttp://hdl.handle.net/11536/2784-
dc.description.abstractA method is described for enlarging as much as possible the basin of attraction of a Hopfield-type associative memory. The proposed learning rule, a minimum-overlap learning algorithm that includes a threshold parameter, enables a Hopfield-type associative memory to be designed so that the memory will have a maximal basin of attraction. A technique that diminishes the effect of the threshold on the minimum-overlap learning algorithm is devised. Simulation results show that the basin of attraction constructed by the proposed method is indeed larger than that constructed by several well known methods.en_US
dc.language.isoen_USen_US
dc.subjectASSOCIATIVE MEMORIESen_US
dc.subjectNEURAL NETWORKSen_US
dc.titleDESIGN OF HOPFIELD-TYPE ASSOCIATIVE MEMORY WITH MAXIMAL BASIN OF ATTRACTIONen_US
dc.typeArticleen_US
dc.identifier.journalELECTRONICS LETTERSen_US
dc.citation.volume29en_US
dc.citation.issue24en_US
dc.citation.spage2128en_US
dc.citation.epage2130en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:A1993NF18500040-
dc.citation.woscount5-
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