Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/60598
DC FieldValueLanguage
dc.contributorDepartment of Electrical Engineering-
dc.creatorChow, KM-
dc.creatorRad, AB-
dc.creatorTsang, KM-
dc.date.accessioned2016-12-19T08:52:31Z-
dc.date.available2016-12-19T08:52:31Z-
dc.identifier.issn1079-8587-
dc.identifier.urihttp://hdl.handle.net/10397/60598-
dc.language.isoenen_US
dc.publisherAutoSoft Pressen_US
dc.subjectFuzzy Data Window Memoryen_US
dc.subjectFuzzy identificationen_US
dc.subjectGenetic algorithmsen_US
dc.titleFuzzy data window memory and its application to system identification by GAen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage13-
dc.identifier.epage22-
dc.identifier.volume9-
dc.identifier.issue1-
dc.identifier.doi10.1080/10798587.2000.10642838-
dcterms.abstractIn this paper, an approach for storing and retrieving the past data by means of a novel Fuzzy Data Window Memory (FDWM) is reported. The data, which is selected for memorization, is based on the highest firing strength of the fuzzy rule. The size of the proposed FDWM is much smaller than traditional window memory with no degradation in performance. A computer simulation study of one of the applications of the proposed FDWM is reported which uses the FDWM to reduce the training data set that will be used in the evaluation module in system identification by Genetic Algorithms (GA).-
dcterms.bibliographicCitationIntelligent automation and soft computing, 2003, v. 9, no. 1, p. 13-22-
dcterms.isPartOfIntelligent automation and soft computing-
dcterms.issued2003-
dc.identifier.eissn2326-005X-
dc.identifier.rosgroupidr12905-
dc.description.ros2002-2003 > Academic research: refereed > Publication in refereed journal-
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