Centroid of a type-2 fuzzy set
Information Sciences: an International Journal
Efficient triangular type-2 fuzzy logic systems
International Journal of Approximate Reasoning
Rough neuro-fuzzy structures for classification with missing data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy relational classifier trained by fuzzy clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
IEEE Transactions on Fuzzy Systems
Discrete Interval Type 2 Fuzzy System Models Using Uncertainty in Learning Parameters
IEEE Transactions on Fuzzy Systems
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In this paper we combine type-2 fuzzy logic with a relational fuzzy system paradigm. Incorporating type-2 fuzzy sets brings new possibilities for performance improvement. The relational fuzzy system scheme reduces significantly the number of system parameters to be trained. Numerical simulations of the proposed combination of systems are presented.