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dc.contributor.authorChang, RIen_US
dc.contributor.authorHsiao, PYen_US
dc.date.accessioned2014-12-08T15:01:08Z-
dc.date.available2014-12-08T15:01:08Z-
dc.date.issued1998-01-01en_US
dc.identifier.issn1065-514Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/48-
dc.description.abstractIn this paper, a new optimization technique called SOFT (self-organizing fuzzy technique) is proposed to solve the macro-cell placement problem. In SOFT, different criteria are simultaneously accounted by a novel fuzzy gain function which models expert knowledge to control the optimization process. The presented procedure is an adaptation of Kohonen's self-organization algorithm which is well suited for implementation on massively parallel architecture for fast computing. The MCNC benchmark examples are presented to verify the performance and feasibility of SOFT. Comparisons are made with the Hopfield network, SOAP and TimberWolf MC5.6. Experiments show that the proposed method yields an average of 17% improvement in total wire length compared with previous methods. Large size problems with 225 and 1024 arbitrarily-sized macrocells are also presented.en_US
dc.language.isoen_USen_US
dc.subjectcustom-chip designen_US
dc.subjectmacro-cell placementen_US
dc.subjectself-organizationen_US
dc.subjectfuzzy seten_US
dc.subjectneural networksen_US
dc.subjectoptimizationen_US
dc.titleMacro-cell placement fos custom-chip design using self-organizing fuzzy techniqueen_US
dc.typeArticleen_US
dc.identifier.journalVLSI DESIGNen_US
dc.citation.volume7en_US
dc.citation.issue4en_US
dc.citation.spage385en_US
dc.citation.epage399en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
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