Some New Implication Operations Emerging From Fuzzy Logic

We choose, from fuzzy set theory, t-norms, t-conorms and fuzzy compliments which forms dual triplet that is (i,u,c) that satisfy the DeMorgan's law, these dual triplet are used in the construction of fuzzy implications in fuzzy logic. In this work introduction of fuzzy implication is given, which included definition of fuzzy implications and their properties and also distinct classes of fuzzy implication (S, R and QL-implications). Further also described previous work on fuzzy implication and supporting literature of construction of fuzzy implication are given. Finally main contribution of work is to design new fuzzy implication and their graphical representations

An extension of the ordering based on nullnorms

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 $F$-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 of strong implications over conjunctive and disjunctive uninorms

summary:This paper deals with implications defined from disjunctive uninorms $U$ by the expression $I(x,y)=U(N(x),y)$ where $N$ is a strong negation. The main goal is to solve the functional equation derived from the distributivity condition of these implications over conjunctive and disjunctive uninorms. Special cases are considered when the conjunctive and disjunctive uninorm are a $t$-norm or a $t$-conorm respectively. The obtained results show a lot of new solutions generalyzing those obtained in previous works when the implications are derived from $t$-conorms

Homomorphisms on the monoid of fuzzy implications and the iterative functional equation I(x,I(x,y))=I(x,y)

Recently, Vemuri and Jayaram proposed a novel method of generating fuzzy implications, called the ⊛⊛-composition, from a given pair of fuzzy implications [Representations through a Monoid on the set of Fuzzy Implications, Fuzzy Sets and Systems, 247, 51-67]. However, as with any generation process, the ⊛⊛-composition does not always generate new fuzzy implications. In this work, we study the generative power of the ⊛⊛-composition. Towards this end, we study some specific functional equations all of which lead to the solutions of the iterative functional equation I(x,I(x,y))=I(x,y)I(x,I(x,y))=I(x,y) involving fuzzy implications which has been studied extensively for different families of fuzzy implications in this very journal, see [Information Sciences 177, 2954–2970 (2007); 180, 2487–2497 (2010); 186, 209–221 (2012)]. In this work, unlike in other existing works, we do not restrict the solutions to a particular family of fuzzy implications. Thus we take an algebraic approach towards solving these functional equations. Viewing the ⊛⊛-composition as a binary operation ⊛⊛ on the set II of all fuzzy implications one obtains a monoid structure (I,⊛)(I,⊛) on the set II. From the Cayley’s theorem for monoids, we know that any monoid is isomorphic to the set of all right translations. We determine the complete set KK of fuzzy implications w.r.t. which the right translations also become semigroup homomorphisms on the monoid (I,⊛I,⊛) and show that KK not only answers our questions regarding the generative power of the ⊛⊛-composition but also contains many as yet unknown solutions of the iterative functional equation I(x,I(x,y))=I(x,y)I(x,I(x,y))=I(x,y)

On the distributivity of T-power based implications

Due to the fact that Zadeh's quantifiers constitute the usual method to modify fuzzy propositions, the so-called family of T-power based implications was proposed. In this paper, the four basic distributive laws related to T-power based fuzzy implications and fuzzy logic operations (t-norms and t-conorms) are deeply studied. This study shows that two of the four distributive laws of the T-power based implications have a unique solution, while the other two have multiple solutions

A Deep Study of Fuzzy Implications

This thesis contributes a deep study on the extensions of the IMPLY operator in classical binary logic to fuzzy logic, which are called fuzzy implications. After the introduction in Chapter 1 and basic notations about the fuzzy logic operators In Chapter 2 we first characterize In Chapter 3 S- and R- implications and then extensively investigate under which conditions QL-implications satisfy the thirteen fuzzy implication axioms. In Chapter 4 we develop the complete interrelationships between the eight supplementary axioms FI6-FI13 for fuzzy implications satisfying the five basic axioms FI1-FI15. We prove all the dependencies between the eight fuzzy implication axioms, and provide for each independent case a counter-example. The counter-examples provided in this chapter can be used in the applications that need different fuzzy implications satisfying different fuzzy implication axioms. In Chapter 5 we study proper S-, R- and QL-implications for an iterative boolean-like scheme of reasoning from classical binary logic in the frame of fuzzy logic. Namely, repeating antecedents $n$ times, the reasoning result will remain the same. To determine the proper S-, R- and QL-implications we get a full solution of the functional equation $I(x,y)=I(x,I(x,y))$, for all $x$, $y\in[0,1]$. In Chapter 6 we study for the most important t-norms, t-conorms and S-implications their robustness against different perturbations in a fuzzy rule-based system. We define and compare for these fuzzy logical operators the robustness measures against bounded unknown and uniform distributed perturbations respectively. In Chapter 7 we use a fuzzy implication $I$ to define a fuzzy $I$-adjunction in $\mathcal{F}(\mathbb{R}^{n})$. And then we study the conditions under which a fuzzy dilation which is defined from a conjunction $\mathcal{C}$ on the unit interval and a fuzzy erosion which is defined from a fuzzy implication $I^{'}$ to form a fuzzy $I$-adjunction. These conditions are essential in order that the fuzzification of the morphological operations of dilation, erosion, opening and closing obey similar properties as their algebraic counterparts. We find out that the adjointness between the conjunction $\mathcal{C}$ on the unit interval and the implication $I$ or the implication $I^{'}$ play important roles in such conditions

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

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

O równaniach funkcyjnych związanych z rozdzielnością implikacji rozmytych

In classical logic conjunction distributes over disjunction and disjunction distributes over conjunction. Moreover, implication is left-distributive over conjunction and disjunction: p ! (q ^ r) (p ! q) ^ (p ! r); p ! (q _ r) (p ! q) _ (p ! r): At the same time it is neither right-distributive over conjunction nor over disjunction. However, the following two equalities, that are kind of right-distributivity of implications, hold: (p ^ q) ! r (p ! r) _ (q ! r); (p _ q) ! r (p ! r) ^ (q ! r): We can rewrite the above four classical tautologies in fuzzy logic and obtain the following distributivity equations: I(x;C1(y; z)) = C2(I(x; y); I(x; z)); (D1) I(x;D1(y; z)) = D2(I(x; y); I(x; z)); (D2) I(C(x; y); z) = D(I(x; z); I(y; z)); (D3) I(D(x; y); z) = C(I(x; z); I(y; z)); (D4) that are satisfied for all x; y; z 2 [0; 1], where I is some generalization of classical implication, C, C1, C2 are some generalizations of classical conjunction and D, D1, D2 are some generalizations of classical disjunction. We can define and study those equations in any lattice L = (L;6L) instead of the unit interval [0; 1] with regular order „6” on the real line, as well. From the functional equation’s point of view J. Aczél was probably the one that studied rightdistributivity first. He characterized solutions of the functional equation (D3) in the case of C = D, among functions I there are bounded below and functions C that are continuous, increasing, associative and have a neutral element. Part of the results presented in this thesis may be seen as a generalization of J. Aczél’s theorem but with fewer assumptions on the functions F and G. As a generalization of classical implication we consider here a fuzzy implication and as a generalization of classical conjunction and disjunction - t-norms and t-conorms, respectively (or more general conjunctive and disjunctive uninorms). We study the distributivity equations (D1) - (D4) for such operators defined on different lattices with special focus on various functional equations that appear. In the first two sections necessary fuzzy logic concepts are introduced. The background and history of studies on distributivity of fuzzy implications are outlined, as well. In Sections 3, 4 and 5 new results are presented and among them solutions to the following functional equations (with different assumptions): f(m1(x + y)) = m2(f(x) + f(y)); x; y 2 [0; r1]; g(u1 + v1; u2 + v2) = g(u1; u2) + g(v1; v2); (u1; u2); (v1; v2) 2 L1; h(xc(y)) = h(x) + h(xy); x; y 2 (0;1); k(min(j(y); 1)) = min(k(x) + k(xy); 1); x 2 [0; 1]; y 2 (0; 1]; where: f : [0; r1] ! [0; r2], for some constants r1; r2 that may be finite or infinite, and for functions m2 that may be injective or not; g : L1 ! [1;1], for L1 = f(u1; u2) 2 [1;1]2 j u1 u2g (function g satisfies two-dimensional Cauchy equation extended to the infinities); h; c : (0;1) ! (0;1) and function h is continuous or is a bijection; k : [0; 1] ! [0; 1], g : (0; 1] ! [1;1) and function k is continuous. Most of the results in Sections 3, 4 and 5 are new and obtained by the author in collaboration with M. Baczynski, R. Ger, M. E. Kuczma or T. Szostok. Part of them have been already published either in scientific journals (see [5]) or in refereed papers in proceedings (see [4, 1, 2, 3])