14 research outputs found

    On the distributivity equation for uni-nullnorms

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    summary:A uni-nullnorm is a special case of 2-uninorms obtained by letting a uninorm and a nullnorm share the same underlying t-conorm. This paper is mainly devoted to solving the distributivity equation between uni-nullnorms with continuous Archimedean underlying t-norms and t-conorms and some binary operators, such as, continuous t-norms, continuous t-conorms, uninorms, and nullnorms. The new results differ from the previous ones about the distributivity in the class of 2-uninorms, which have not yet been fully characterized

    An extension of the ordering based on nullnorms

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    summary:In this paper, we generally study an order induced by nullnorms on bounded lattices. We investigate monotonicity property of nullnorms on bounded lattices with respect to the FF-partial order. Also, we introduce the set of incomparable elements with respect to the F-partial order for any nullnorm on a bounded lattice. Finally, we investigate the relationship between the order induced by a nullnorm and the distributivity property for nullnorms

    Distributivity between extended nullnorms and uninorms on fuzzy truth values

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    This paper mainly investigates the distributive laws between extended nullnorms and uninorms on fuzzy truth values under the condition that the nullnorm is conditionally distributive over the uninorm. It presents the distributive laws between the extended nullnorm and t-conorm, and the left and right distributive laws between the extended generalization nullnorm and uninorm, where a generalization nullnorm is an operator from the class of aggregation operators with absorbing element that generalizes a nullnorm.Comment: 2

    Migrativity properties of 2-uninorms over semi-t-operators

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    summary:In this paper, we analyze and characterize all solutions about α\alpha-migrativity properties of the five subclasses of 2-uninorms, i. e. CkC^{k}, Ck0C^{0}_{k}, Ck1C^{1}_{k}, C10C^{0}_{1}, C01C^{1}_{0}, over semi-t-operators. We give the sufficient and necessary conditions that make these α\alpha-migrativity equations hold for all possible combinations of 2-uninorms over semi-t-operators. The results obtained show that for G∈CkG\in C^{k}, the α\alpha-migrativity of GG over a semi-t-operator Fμ,νF_{\mu,\nu} is closely related to the α\alpha-section of Fμ,νF_{\mu,\nu} or the ordinal sum representation of t-norm and t-conorm corresponding to Fμ,νF_{\mu,\nu}. But for the other four categories, the α\alpha-migrativity over a semi-t-operator Fμ,νF_{\mu,\nu} is fully determined by the α\alpha-section of Fμ,νF_{\mu,\nu}

    Fitting aggregation operators to data

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    Theoretical advances in modelling aggregation of information produced a wide range of aggregation operators, applicable to almost every practical problem. The most important classes of aggregation operators include triangular norms, uninorms, generalised means and OWA operators.With such a variety, an important practical problem has emerged: how to fit the parameters/ weights of these families of aggregation operators to observed data? How to estimate quantitatively whether a given class of operators is suitable as a model in a given practical setting? Aggregation operators are rather special classes of functions, and thus they require specialised regression techniques, which would enforce important theoretical properties, like commutativity or associativity. My presentation will address this issue in detail, and will discuss various regression methods applicable specifically to t-norms, uninorms and generalised means. I will also demonstrate software implementing these regression techniques, which would allow practitioners to paste their data and obtain optimal parameters of the chosen family of operators.<br /

    Distributivity of ordinal sum implications over overlap and grouping functions

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    summary:In 2015, a new class of fuzzy implications, called ordinal sum implications, was proposed by Su et al. They then discussed the distributivity of such ordinal sum implications with respect to t-norms and t-conorms. In this paper, we continue the study of distributivity of such ordinal sum implications over two newly-born classes of aggregation operators, namely overlap and grouping functions, respectively. The main results of this paper are characterizations of the overlap and/or grouping function solutions to the four usual distributive equations of ordinal sum fuzzy implications. And then sufficient and necessary conditions for ordinal sum implications distributing over overlap and grouping functions are given

    Invariability, orbits and fuzzy attractors

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    In this paper, we present a generalization of a new systemic approach to abstract fuzzy systems. Using a fuzzy relations structure will retain the information provided by degrees of membership. In addition, to better suit the situation to be modelled, it is advisable to use T-norm or T-conorm distinct from the minimum and maximum, respectively. This gain in generality is due to the completeness of the work on a higher level of abstraction. You cannot always reproduce the results obtained previously, and also sometimes different definitions with different views are obtained. In any case this approach proves to be much more effective when modelling reality

    Aggregation functions: Means

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    The two-parts state-of-art overview of aggregation theory summarizes the essential information concerning aggregation issues. Overview of aggregation properties is given, including the basic classification of aggregation functions. In this first part, the stress is put on means, i.e., averaging aggregation functions, both with fixed arity (n-ary means) and with open arity (extended means).

    Contribució a l'estudi de les uninormes en el marc de les equacions funcionals.

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    Les uninormes són uns operadors d'agregació que, per la seva definició, es poden considerar com a conjuncions o disjuncions, i que han estat aplicades a camps molt diversos. En aquest treball s'estudien algunes equacions funcionals que tenen com a incògnites les uninormes, o operadors definits a partir d'elles. Una d'elles és la distributivitat, que és resolta per les classes d'uninormes conegudes, solucionant, en particular, un problema obert en la teoria de l'anàlisi no-estàndard. També s'estudien les implicacions residuals i fortes definides a partir d'uninormes, trobant solució a la distributivitat d'aquestes implicacions sobre uninormes. Com a aplicació d'aquests estudis, es revisa i s'amplia la morfologia matemàtica borrosa basada en uninormes, que proporciona un marc inicial favorable per a un nou enfocament en l'anàlisi d'imatges, que haurà de ser estudiat en més profunditat.Las uninormas son unos operadores de agregación que, por su definición se pueden considerar como conjunciones o disjunciones y que han sido aplicados a campos muy diversos. En este trabajo se estudian algunas ecuaciones funcionales que tienen como incógnitas las uninormas, o operadores definidos a partir de ellas. Una de ellas es la distributividad, que se resuelve para las classes de uninormas conocidas, solucionando, en particular, un problema abierto en la teoría del análisis no estándar. También se estudian las implicaciones residuales y fuertes definidas a partir de uninormas, encontrando solución a la distributividad de estas implicaciones sobre uninormas. Como aplicación de estos estudios, se revisa y amplía la morfología matemática borrosa basada en uninormas, que proporciona un marco inicial favorable para un nuevo enfoque en el análisis de imágenes, que tendrá que ser estudiado en más profundidad.Uninorms are aggregation operators that, due to its definition, can be considered as conjunctions or disjunctions, and they have been applied to very different fields. In this work, some functional equations are studied, involving uninorms, or operators defined from them as unknowns. One of them is the distributivity equation, that is solved for all the known classes of uninorms, finding solution, in particular, to one open problem in the non-standard analysis theory. Residual implications, as well as strong ones defined from uninorms are studied, obtaining solution to the distributivity equation of this implications over uninorms. As an application of all these studies, the fuzzy mathematical morphology based on uninorms is revised and deeply studied, getting a new framework in image processing, that it will have to be studied in more detail
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