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An Interval Approach to Fuzzistics for Interval Type-2 Fuzzy Sets

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2 Author(s)
Feilong Liu ; Student Member, IEEE, Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089-2564, USA. phone: 213-740-4456; fax: 213-740-4651; email: ; Jerry M. Mendel

In this paper, a new and simple approach, called interval approach, to type-2 fuzzistics is presented, one that captures the strong points of both the person-MF and interval end-points approaches. It uses interval end-point data that are collected from a group of subjects, assumes a probability distribution for each person's data and maps the mean and standard deviation of that distribution into the parameters of an iteratively specified type-1 person MF. These type-1 person MFs are then aggregated using the union leading to the FOU for a word. Experiments show that this approach is easy to implement and the derived interval type-2 word models match our intuitions, i.e., the FOUs of the small-sounding words are located to the left, the FOUs of the medium-sounding words are located in the middle, and the FOUs of the large-sounding words are located to the right.

Published in:

2007 IEEE International Fuzzy Systems Conference

Date of Conference:

23-26 July 2007