Gebhardt, Albrecht On types of fuzzy numbers and extension principles. (English) Zbl 0864.26010 Fuzzy Sets Syst. 75, No. 3, 311-318 (1995). A real function \(f\) often is fuzzified into a fuzzy function \(F\) in such a way that the arguments of \(F\) become fuzzy numbers and its values are determined from \(f\) via the extension principle \(EP\). In general, \(EP\) depends on a \(t\)-norm \(T\). Restricting furthermore the input fuzzy numbers to symmetric \(LR\)-fuzzy numbers with \(L=R\), the fuzzification of \(f\) depends of the pair \((L,T)\).The author discusses the problem whether different such fuzzifications may yield the same fuzzy function \(F\). Reviewer: S.Gottwald (Leipzig) Cited in 5 Documents MSC: 26E50 Fuzzy real analysis 94D05 Fuzzy sets and logic (in connection with information, communication, or circuits theory) Keywords:fuzzy functions; \(t\)-norm; extension principle; fuzzy numbers PDFBibTeX XMLCite \textit{A. Gebhardt}, Fuzzy Sets Syst. 75, No. 3, 311--318 (1995; Zbl 0864.26010) Full Text: DOI References: [1] Bandemer, H.; Näther, W., Fuzzy Data Analysis (1992), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht · Zbl 0758.62003 [2] Dubois, D.; Prade, H., Fuzzy Sets and Systems: Theory and Applications (1980), Academic Press: Academic Press New York · Zbl 0444.94049 [3] Otto, K. N.; Lewis, A. D.; Antonsson, E. K., Approximating α-cuts with the vertex method, Fuzzy Sets and Systems, 55, 43-50 (1993) · Zbl 0931.26010 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.