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In this paper, an extended ANFIS architecture is proposed. By incorporating an extra layer for the fuzzification process, the extended architecture is able to fit both type-1 and interval type-2 models. The learning properties of the proposed architecture based on the least-squares estimate method are studied on selected type-1 and interval type-2 ANFIS models. We show that the least-squares estimate...
In previous work the Authors defined the alpha-cut representation for type-2 fuzzy sets. The strength of this representation is that it allows type-2 fuzzy sets to be fully defined by a collection of crisp sets. Each of these crisp sets may be independently processed within a fuzzy logic system prior to defuzzification. This independence means this representation is ideal for parallel implementation...
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