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Proceedings Paper

Generalized regression for fuzzy rule bases using the Hough transform
Author(s): Joseph M. Barone; Dimitar P. Fileu
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Paper Abstract

The extended Hough transform permits weight functions of arbitrary type and complexity to help guide the choice of a `regression' line in polar coordinate space. This paper suggests that this transform may be helpful in locating the best linear approximation to gaps and areas of conflict in fuzzy rule bases. Using the sliding mode approximation of a fuzzy controller as an example, this paper shows how global properties of the rule base can be used to help guide the search for good approximations. The notion of `representativeness' of centroids and its effect on regression via the Hough transform is also considered. Finally, a different approach based on OWA operators is discussed briefly.

Paper Details

Date Published: 22 December 1993
PDF: 12 pages
Proc. SPIE 2061, Applications of Fuzzy Logic Technology, (22 December 1993); doi: 10.1117/12.165035
Show Author Affiliations
Joseph M. Barone, Loki Software, Inc. (United States)
Dimitar P. Fileu, Iona College (United States)


Published in SPIE Proceedings Vol. 2061:
Applications of Fuzzy Logic Technology
Bruno Bosacchi; James C. Bezdek, Editor(s)

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