On a class of distributive fuzzy implications
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - Special issue on aggregation operators
Contrapositive symmetry of distributive fuzzy implications
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
On some new classes of implication operators and their role in approximate reasoning
Information Sciences—Informatics and Computer Science: An International Journal
Information Sciences: an International Journal
Distributivity of residual implications over conjunctive and disjunctive uninorms
Fuzzy Sets and Systems
On the characterizations of (S,N)-implications
Fuzzy Sets and Systems
On the distributivity of fuzzy implications over nilpotent or strict triangular conorms
IEEE Transactions on Fuzzy Systems
Combinatorial rule explosion eliminated by a fuzzy rule configuration
IEEE Transactions on Fuzzy Systems
Comments on “Combinatorial rule explosion eliminated by a fuzzy rule configuration” [and reply]
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Comment on “Combinatorial rule explosion eliminated by a fuzzy rule configuration” [and reply]
IEEE Transactions on Fuzzy Systems
On the law [p∧q→r]=[(p→r)V(q→r)] in fuzzy logic
IEEE Transactions on Fuzzy Systems
On the distributivity of implication operators over T and S norms
IEEE Transactions on Fuzzy Systems
International Journal of Approximate Reasoning
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Recently, we have examined solutions of the following distributive functional equation I(x, S1(y, z)) = S2(I(x, y), I(x, z)), when S1, S2 are continuous Archimedean t-conorms and I is an unknown function [5,3]. Earlier, in [1,2], we have also discussed solutions of the following distributive equation I(x, T1(y, z)) = T2(I(x, y), I(x, z)), when T1, T2 are strict t-norms. In particular, in both cases, we have presented solutions which are fuzzy implications in the sense of Fodor and Roubens. In this paper we continue these investigations for the situation when T1, T2 are continuous Archimedean t-norms, thus we give a partial answer for one open problem postulated in [2]. Obtained results are not only theoretical - they can be also useful for the practical problems, since such distributive equations have an important role to play in efficient inferencing in approximate reasoning, especially in fuzzy control systems.