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

Arabshahi, P.; Marks, R. J.; Oh, S.; Caudell, T. P.; Choi, J. J.; Song, B. G.

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