Aggregation operators and additive generators
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - Special issue on aggregation operators
Construction of kernel aggregation operators from marginal values
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Aggregation operators: properties, classes and construction methods
Aggregation operators
Modeling Decisions: Information Fusion and Aggregation Operators (Cognitive Technologies)
Modeling Decisions: Information Fusion and Aggregation Operators (Cognitive Technologies)
Aggregation Functions: A Guide for Practitioners
Aggregation Functions: A Guide for Practitioners
Lipschitzian De Morgan triplets of fuzzy connectives
Information Sciences: an International Journal
Stability of weighted penalty-based aggregation functions
Fuzzy Sets and Systems
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This article discusses Lipschitz properties of generated aggregation functions. Such generated functions include triangular norms and conorms, quasi-arithmetic means, uninorms, nullnorms and continuous generated functions with a neutral element. The Lipschitz property guarantees stability of aggregation operations with respect to input inaccuracies, and is important for applications. We provide verifiable sufficient conditions to determine when a generated aggregation function holds the k-Lipschitz property, and calculate the Lipschitz constants of power means. We also establish sufficient conditions which guarantee that a generated aggregation function is not Lipschitz. We found the only 1-Lipschitz generated function with a neutral element e@?]0,1[.