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Pointer Adaptation and Pruning of Min-Max Fuzzy Inference and Estimation

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dc.contributor.author Arabshahi, P. en_US
dc.contributor.author Marks, R. J. en_US
dc.contributor.author Oh, S. en_US
dc.contributor.author Caudell, T. P. en_US
dc.contributor.author Choi, J. J. en_US
dc.contributor.author Song, B. G. en_US
dc.date.accessioned 2004-09-27T17:30:59Z
dc.date.available 2004-09-27T17:30:59Z
dc.date.issued 1997-10 en_US
dc.identifier.citation USA en_US
dc.identifier.clearanceno 97-1441 en_US
dc.identifier.uri http://hdl.handle.net/2014/22900
dc.description.abstract A new technique for adaptation of fuzzy membership functions in a fuzzy inference system is proposed. The pointer technique relies upon the isolation of the specific membership functions that contributed to the final decision, followed by the updating of these functions' parameters using steepset descent. en_US
dc.format.extent 1332491 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject.other Fuzzy Inference en_US
dc.title Pointer Adaptation and Pruning of Min-Max Fuzzy Inference and Estimation en_US


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