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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1927

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dc.contributor.authorFazle Azeem, M-
dc.contributor.authorHanmandlu, M-
dc.contributor.authorAhmad, N-
dc.date.accessioned2006-07-03T04:32:24Z-
dc.date.available2006-07-03T04:32:24Z-
dc.date.issued1998-
dc.identifier.citationTENCON IEEE Region 10 International Conference on Global Connectivity in Energy, Computer, Communication and Control, 1, 230 - 233p.en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/1927-
dc.description.abstractThe concept of the approximate fuzzy data model (AFDM) is introduced. An attempt is made for input variable identification for fuzzy modeling of dynamical systems using the fuzzy curve, which is the output of AFDM. An output ratio is defined based on AFDM and system output that gives rise to the proposed criteria whose effectiveness is demonstrated by experimentation on mathematical models as well as by simulation on a few examples of dynamical systems. The proposed criteria thus serve as a significance test for the identification of inputs that actually affect the outputen
dc.format.extent42584 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectapproximate fuzzy data modelen
dc.subjectdynamical systemsen
dc.titleA new criteria for input variable identification of dynamical systemsen
dc.typeArticleen
Appears in Collections:Electrical Engineering

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