We define a binary operation T1⋆T2 on the fuzzy unit interval \I by extending the natural action of T1 and T2 on step functions. When both T1 and T2 are left-continuous, this operation coincides with the tensor product of the corresponding quantales and therefore yields a t-norm on \I. Without left-continuity, the situation becomes more subtle. We prove that if at least one of the two t-norms is continuous, then T1⋆T2 is still a t-norm on \I. We also show by counterexample that continuity cannot simply be dropped. The operation \DN fails to be associative. On the other hand, TD⋆TD is a t-norm despite TD being neither continuous nor left-continuous, indicating that continuity is not a necessary condition.
Introduction
Triangular norms, or t-norms, are associative, commutative, non-decreasing binary operations on the real unit interval [0,1] with neutral element 1. They were introduced in 1963 by Schweizer and Sklar [17, 18] to formulate the triangle inequality in probabilistic metric spaces. In fuzzy set theory, t-norms have been extensively used to model fuzzy intersections [1, 16] and conjunction operators in fuzzy logic [6, 11].
In 1967, Goguen introduced L-fuzzy sets [8], where the codomain of a fuzzy set is a partially ordered set (poset) L. Noting that the definition of a t-norm on [0,1] can be naturally extended to any bounded poset, De Cooman and Kerre generalized the concept of t-norms to bounded posets [5], thereby providing fuzzy intersection operators for Goguen’s L-fuzzy sets.
Following Goguen’s general framework, many different types of posets L have been employed as codomains of fuzzy sets. Among these, an important class consists of posets into which the unit interval [0,1] can be embedded as a subset, because such posets allow a more precise description of concepts with subtle fuzzy features. A prominent example is Zadeh’s type-2 fuzzy sets [20, 21], where the codomain is taken to be the set M=[0,1][0,1] of all fuzzy subsets of [0,1]. To extend the usual order on [0,1] to M, two compatible partial orders ⊑⊓ and ⊑⊔ were introduced on M, yielding the posets (M,⊑⊓) and (M,⊑⊔)[12]. Also in [12], the authors lifted t-norms on [0,1] to binary operations on these two posets by using the meet operation ∧ on the codomain [0,1].
In fuzzy topology, Hutton introduced the fuzzy unit interval I(L) in 1975 as a lattice-theoretic extension of the real unit interval, where L is a complete lattice [13]. In the special case L=[0,1], the fuzzy unit interval can be characterized equivalently as the collection of all right-continuous non-increasing functions f:[0,1]⟶[0,1] satisfying f(1)=0, which forms a subset of M. We denote this particular fuzzy unit interval by I. Endowed with the pointwise order, I is a subposet of M.
In fact, I enjoys even stronger structural properties. The unit interval [0,1] embeds into I as a complete sublattice, and I is precisely the tensor product of [0,1] with itself in the category SUP, whose objects are complete lattices and whose morphisms are supremum-preserving maps. Consequently, t-norms on I can be constructed by forming the tensor product of two quantales with the same underlying set [0,1][7, 9, 10]. Recall that ([0,1],T) is a quantale if and only if T is left-continuous. Thus, the quantale tensor product construction of a t-norm on I requires both input t-norms to be left-continuous. This observation leads to a natural question: given two arbitrary t-norms T1 and T2 on [0,1] that are not necessarily left-continuous, can one still construct a t-norm on I from them?
In this paper, we give sufficient conditions under which this construction yields a t-norm. We present a general method for constructing a binary operation T1⋆T2 on I starting from two arbitrary t-norms T1 and T2 on [0,1]. When both t-norms are left-continuous, this operation coincides with the quantale tensor product construction already known in the literature; the existence of the resulting unital quantale follows from [9 Theorem 4.2]. Our proof in this case is a direct verification for the unit interval, rather than a new tensor-product construction. We then prove that T1⋆T2 is a t-norm on I whenever at least one of T1, T2 is continuous. We also provide examples illustrating two complementary phenomena: on the one hand, if neither component t-norm is continuous, T1⋆T2 need not be associative and may therefore fail to be a t-norm on I; on the other hand, although the drastic product t-norm TD is neither continuous nor left-continuous, TD⋆TD is still a t-norm on I.
The main associativity theorem goes beyond the case of two left-continuous components because the second component may fail left-continuity when the first is continuous. The pair (TD,TD) shows that both components may fail left-continuity, whereas (TD,TnM) shows that left-continuity of only one component does not suffice. These results provide sufficient conditions and contrasting examples, not a classification of all admissible pairs.
The paper is organized as follows. Section 2 recalls basic notions concerning fuzzy unit intervals and t-norms on [0,1]. In Section 3 we introduce the operation T1⋆T2, establish its fundamental properties, and discuss its Archimedean-type properties. Section 4 is devoted to proving our main result: if either T1 or T2 is continuous, then T1⋆T2 is a t-norm on I; two important examples are also discussed there. Section 5 concludes the paper and outlines directions for future work.
Preliminaries
Unless explicitly stated otherwise, (P,≤) denotes a bounded partially ordered set. Its bottom and top elements are denoted by ⊥ and ⊤, respectively. We always assume that ⊥=⊤.
Equipped with the usual order of real numbers, the unit interval [0,1] is a bounded partially ordered set with ⊥=0 and ⊤=1. It is also a complete lattice. For a subset A⊆[0,1], we write supA and infA for the least upper bound and greatest lower bound of A, respectively. In particular, sup∅=0 and inf∅=1.
Let f:[0,1]⟶[0,1] be a non-increasing function. Define
f(t−)=s<tinff(s),f(t+)=s>tsupf(s)
for all t∈[0,1]. In particular,
f(0−)=inf∅=1,f(1+)=sup∅=0.
Hutton’s fuzzy unit interval [13] is defined by taking a general complete lattice L as the codomain of the fuzzy sets. In the present paper we restrict to the case L=[0,1].
Definition 2.1. Let MR be the set of all non-increasing maps λ:[0,1]⟶[0,1] with λ(0)=1 and λ(1)=0. Let ∼ be an equivalence relation on MR given by
λ∼μ⟺∀t∈[0,1],λ(t−)=μ(t−),λ(t+)=μ(t+).
The quotient set MR/∼ is called the fuzzy unit interval.
We denote by I the collection of all right-continuous non-increasing maps f:[0,1]⟶[0,1] satisfying f(1)=0. Then a map f:[0,1]⟶[0,1] belongs to I if and only if f(infA)=supf(A) for all A⊆[0,1].
Proposition 2.2. *There is a bijection between the set I and the quotient set MR/∼.
Proof. Given an element λ∈MR, let λˉ(t)=λ(t+) for all t∈[0,1]. Then λˉ∈I. We first show that the map [λ]↦λˉ is well-defined from MR/∼ to I. By the definition of the equivalence relation ∼ on MR, if λ∼μ, then clearly λˉ=μˉ. Thus, the assignment is independent of the choice of representatives.
To prove injectivity, assume [λ]=[μ]. By the definition of ∼, either λ(t0+)=μ(t0+) or λ(t0−)=μ(t0−) for some t0∈[0,1]. We consider two cases:
If λ(t0+)=μ(t0+) for some t0, then clearly λˉ=μˉ.
If λ(t0−)=μ(t0−) for some t0, without loss of generality assume λ(t0−)<μ(t0−). Choose δ>0 such that for all t∈(t0−δ,t0),
λ(t)<2λ(t0−)+μ(t0−)<μ(t).
For all t∈(t0−δ,t0), since μ(t) is greater than the constant 2λ(t0−)+μ(t0−), we have 2λ(t0−)+μ(t0−)≤μ(t+). Consequently, for all t∈(t0−δ,t0),
λ(t+)≤λ(t)<2λ(t0−)+μ(t0−)≤μ(t+),
which implies λˉ=μˉ.
Thus, the map is injective.
For surjectivity, let λ∈I be arbitrary. Define λ∈MR by
λ(t)={λ(t),1,t>0,t=0.
Then λˉ=λ, showing that the map is also surjective.
Therefore, the assignment [λ]↦λˉ is a bijection as desired.
Definition 2.3. For f∈I, define its adjoint by
f∗(y)=inf{x∈[0,1]:f(x)≤y},y∈[0,1].
The set under the infimum is nonempty because f(1)=0.
Lemma 2.4. For f∈I, the map f∗ is the unique map satisfying
f(x)≤y⟺f∗(y)≤x(x,y∈[0,1]).
Moreover, f∗∈I, (f∗)∗=f, and f≤g if and only if f∗≤g∗.
Proof. Fix y and put Ay={x:f(x)≤y}. Since f takes arbitrary infima to suprema, f(infAy)=supf(Ay)≤y. Thus Ay=[f∗(y),1], proving the equivalence and uniqueness. For every B⊆[0,1] and x∈[0,1], this equivalence gives
Consequently f∗(infB)=supb∈Bf∗(b), including B=∅, and therefore f∗∈I. The symmetry of the adjunction equivalence gives (f∗)∗=f. If f≤g, then {x:g(x)≤y}⊆{x:f(x)≤y}, so f∗≤g∗. Applying this implication to f∗,g∗ proves the converse.
Thus f↦f∗ is an order-preserving involution, hence a complete lattice automorphism.
Step functions play a fundamental role in the structure of I. For r,a∈[0,1], define the step function⟨r,a⟩:[0,1]⟶[0,1] by
⟨r,a⟩(x)={a,0,0≤x<r,r≤x≤1.
Equipped with the pointwise order, I is a complete lattice whose top and bottom elements are ⟨1,1⟩ and ⟨0,0⟩, respectively. Suprema are calculated pointwise: for every family (fi)i∈J⊆I,
(i∈Jsupfi)(x)=i∈Jsupfi(x).
Indeed, the right-hand side is non-increasing, vanishes at 1, and satisfies, for x<1,
It therefore belongs to I and is the least upper bound. This also covers the empty family. Let
E:={⟨r,a⟩∣r,a∈[0,1]}.
The following lemma shows that E is sup-dense in I.
Lemma 2.5. (1) For allf∈Iand all⟨s,a⟩∈E, it holds that
⟨s,a⟩≤f⟺a≤f(s−).(1)
(2) For eachf∈I, it holds that
f=r∈[0,1]sup⟨r,f(r)⟩=r∈(0,1]sup⟨r,f(r−)⟩.(2)
Consequently, for every x∈[0,1],
f(x)=x<rsupf(r−).
Proof. (1) We have
⟨s,a⟩≤f⟺∀x<s,⟨s,a⟩(x)≤f(x)⟺∀x<s,a≤f(x)⟺a≤f(s−).
(2) First, for every x∈[0,1], we have
f(x)=r>xsupf(r)=r>xsup⟨r,f(r)⟩(x)=r∈[0,1]sup⟨r,f(r)⟩(x).(since ∀A⊆[0,1],f(infA)=supf(A))(by the definition of ⟨r,f(r)⟩)(since ⟨r,f(r)⟩(x)=0 if r≤x)
Hence,
f=r∈[0,1]sup⟨r,f(r)⟩.
Second, notice that f(r)≤f(r−) since f is non-increasing. By (1), it holds that
⟨r,f(r)⟩≤⟨r,f(r−)⟩≤f.
Hence,
f=r∈[0,1]sup⟨r,f(r)⟩≤r∈(0,1]sup⟨r,f(r−)⟩≤f,
so f=supr∈(0,1]⟨r,f(r−)⟩. By the definition of step function,
Remark 2.6. A map from the product of two complete lattices to a complete lattice is a bimorphism if it preserves arbitrary suprema in each variable separately, including the empty supremum. The map
ε:[0,1]×[0,1]⟶I,ε(r,a)=⟨r,a⟩,
is a universal bimorphism. To see this directly, the pointwise join formula shows that ε preserves arbitrary suprema in each variable. Given a bimorphism φ:[0,1]×[0,1]⟶L, where L is a complete lattice, define
φˉ(f)=r∈[0,1]supφ(r,f(r)).
For any family (fi)i∈J, preservation of suprema by φ in its second variable gives
Moreover, φ(r,0)=⊥L and preservation in the first variable yield
φˉ(⟨s,a⟩)=r≤ssupφ(r,a)=φ(s,a),
where the case s=0 uses the empty supremum. Hence φˉ∘ε=φ. Uniqueness follows from f=supr⟨r,f(r)⟩ and preservation of suprema. This proves that I, together with ε, realizes the tensor product of [0,1] with itself in SUP [3].
Let b:[0,1]×[0,1]⟶[0,1]⊗[0,1] be the canonical universal bimorphism in a standard tensor-product model, such as those described via Galois connections or lower sets in [9, 19]. The universal properties give a unique complete lattice isomorphism
U:[0,1]⊗[0,1]⟶I,U(b(r,a))=⟨r,a⟩.
Thus ε=U∘b: our map is the canonical universal bimorphism expressed in the step-function realization of the same tensor product. The map ε is not injective, since ⟨r,0⟩=⟨0,a⟩=⊥ for all r,a. Thus ε is not an embedding of the product poset [0,1]×[0,1].
Remark 2.7. Since there exists a bijection between the set MR/∼ and I, we often take I to represent the fuzzy unit interval. In fact, adopting the set I to denote the fuzzy unit interval offers some advantages. Specifically, it allows us to more explicitly reveal its close relationships with the following two mathematical objects.
I is a subset of the codomain of type-2 fuzzy sets. Recall from [12, 20, 21] that the set M=[0,1][0,1], consisting of all fuzzy subsets of [0,1], is the codomain of type-2 fuzzy sets introduced by Zadeh. Clearly, I is a subset of M. Moreover, equipped with the pointwise order on I, the inclusion map I↪M is also an order embedding with respect to both orders ⊑⊓ and ⊑⊔.
I is isomorphic to Δ+. Recall from [18] that Δ+ is the set of all distance distribution functions. That is, for all F∈Δ+, F is a non-decreasing map from [0,∞] to [0,1] such that F(0)=0, F(∞)=1 and F is left-continuous on (0,∞). Notice that x↦−lnx is an isomorphism between ([0,1],≤) and ([0,∞],≥). This order isomorphism gives rise to an isomorphism
Φ:Δ+⟶I,Φ(F)(x)={F(−lnx),F(∞),0<x≤1,x=0.
Definition 2.8.[5] Let (P,≤) be a bounded partially ordered set. A triangular norm, or t-norm, on (P,≤) is a binary operation T:P×P⟶P satisfying the following conditions:
(T1) ∀x∈P,T(x,⊤)=T(⊤,x)=x,
(T2) ∀x,y∈P,T(x,y)=T(y,x),
(T3) ∀x,y,z∈P,T(T(x,y),z)=T(x,T(y,z)),
(T4) ∀x,x′,y,y′∈P,x≤x′,y≤y′⟹T(x,y)≤T(x′,y′).
There are some important basic t-norms on the interval [0,1]; see, e.g., [2, 14]. We list them below:
the nilpotent minimum t-norm: TnM(x,y)={min{x,y},0,x+y>1,x+y≤1.
The t-norms TM, TP and TL are continuous. The nilpotent minimum t-norm TnM is left-continuous but not continuous, whereas the drastic product TD is not left-continuous.
Operations on the fuzzy unit interval induced by pairs of t-norms
Given t-norms T1 and T2 on [0,1], we obtain a binary operation
This prescription is independent of the representation of a step function. Indeed, every nonzero step has unique parameters r,a>0, whereas ⟨r,a⟩=⊥ precisely when r=0 or a=0. Since every t-norm satisfies T(0,t)=0, a zero input always gives the zero step, independently of its parameters. For nonzero steps, ⟨r,a⟩≤⟨s,b⟩ is equivalent to r≤s and a≤b. Consequently the operation on E is monotone. Its commutativity, associativity, and neutral element ⟨1,1⟩ follow from the corresponding properties of T1,T2. Since E is a sup-dense subset of I, the operation T1⋆T2 can be naturally extended to I as follows:
By monotonicity, when both inputs are steps, every term in the supremum is bounded by their product in (3), and that product itself is an admissible term. Thus the extension agrees with (3) on E.
Proposition 3.1. Let T1 and T2 be t-norms on [0,1]. Then
(1) T1⋆T2(f,g)=T1⋆T2(g,f);
(2) If f1≤f2 and g1≤g2, then T1⋆T2(f1,g1)≤T1⋆T2(f2,g2);
(3) T1⋆T2(f,⟨1,1⟩)=f.
Proof. (1) Since both T1 and T2 are commutative, the commutativity of T1⋆T2 follows directly from its definition.
(2) Assume that f1≤f2. For each step function ⟨r,a⟩∈E, if ⟨r,a⟩≤f1 then ⟨r,a⟩≤f2. Therefore, it follows that
The second equality follows from t,b≤1, the monotonicity of T1,T2, and the fact that t=b=1 is admissible. The last equality is Lemma 2.5(2).
Proposition 3.2. Let T1 and T2 be t-norms on [0,1]. Then, for all f,g∈I,
(T1⋆T2(f,g))∗=T2⋆T1(f∗,g∗).
Consequently, f↦f∗ is an order isomorphism (I,T1⋆T2)≅(I,T2⋆T1) that intertwines the two operations.
Proof. Notice that for every step function ⟨r,a⟩∈E, one has
⟨r,a⟩∗=⟨a,r⟩.
Consequently, for every f∈I,
⟨r,a⟩≤f⟺⟨a,r⟩≤f∗.
By Lemma 2.4, the map f↦f∗ is an order-preserving involution, hence an order isomorphism of the complete lattice I. It therefore preserves all suprema. Hence
If both T1 and T2 are left-continuous t-norms, then both ([0,1],T1) and ([0,1],T2) are quantales. Recall from [7, 9, 10] that the monoidal operation T1⊗T2 of the tensor product ([0,1],T1)⊗([0,1],T2) is given by
On the other hand, for any p∈[0,1], if p<T1⋆T2(f,g)(x), then there exists a pair (r,s) with T1(r,s)>x such that p<T2(f(r−),g(s−)). Since T1 is left-continuous, there is a pair (r′,s′) satisfying r′<r, s′<s and x<T1(r′,s′)≤T1(r,s). Thus,
Therefore, we have shown that T1⋆T2=T1⊗T2, as desired.
:::
Remark 3.5. (1) Assume that both T1 and T2 are left-continuous. Notice that the map x↦e−x gives an order isomorphism from ([0,∞],≥) to ([0,1],≤). Hence T1 induces a right-continuous t-conorm L on [0,∞] by
L(x,y)=−ln(T1(e−x,e−y)),
where −ln0=∞ and e−∞=0. For r∈[0,∞] and p∈[0,1], let ηr,p denote the step function written as ε(r,p) in [15 Example 2.7]; explicitly,
ηr,p(x)=⎩⎨⎧1,p,0,x=∞,r<x<∞,0≤x≤r,x<∞.
Recall from Remark 2.7(2) that Φ:Δ+⟶I is the order isomorphism induced by the logarithmic change of variables. Under this identification, Φ(ηr,p)=⟨e−r,p⟩. Therefore the tensor product L⊗T2 on Δ+ is transported to the tensor product T1⊗T2 on I; namely,
Φ((L⊗T2)(F,G))=(T1⊗T2)(Φ(F),Φ(G)),F,G∈Δ+.
Consequently, Theorem 3.4 gives T1⋆T2=T1⊗T2≅L⊗T2. Thus, in the left-continuous case, our operation is precisely the logarithmic counterpart of the tensor-product triangle function investigated in [15]. If, in addition, T1 is continuous, then L is continuous. In this case, [15 Theorem 3.18] implies that τT2,L=L⊗T2 if and only if L satisfies the conditionally strictly increasing property
x<x′,y<y′,L(x′,y′)<∞⟹L(x,y)<L(x′,y′)(LCS)
for all x,x′,y,y′∈[0,∞]. Under this condition, T1⋆T2 also corresponds to the classical Schweizer–Sklar triangle function τT2,L.
(2) Recall from [12] that the convolution of a t-norm T is the operation T:M×M⟶M defined by
T(f,g)(x)=T(r,s)=xsupmin{f(r),g(s)}.
Let T be continuous and satisfy
u<u′,v<v′⟹T(u,v)<T(u′,v′)(u,u′,v,v′∈[0,1]).
Then T⋆TM(f,g)=T(f,g) for all f,g∈I. Indeed, Theorem 3.4 gives
(T⋆TM)(f,g)(x)=T(r,s)>xsupmin{f(r),g(s)}.
For 0≤x<1, continuity of T permits lowering a coordinate until T(r,s)=x, proving that this supremum is at most T(f,g)(x). Conversely, any pair with T(r,s)=x and r,s<1 can be approached from above by pairs with T(rn,sn)>x; right-continuity of f,g gives the reverse inequality. Pairs with r=1 or s=1 contribute zero, and at x=1 both expressions vanish. Consequently, the convolution leaves I invariant and coincides there with T⋆TM.
In what follows, we discuss the Archimedean property of T1⋆T2.
Let T be a t-norm on [0,1]. For each x∈[0,1], define x1=x and xn+1=T(xn,x) for all n≥1. Recall that T is Archimedean if, for all x,y∈(0,1), there exists n≥1 such that xn<y. Equivalently, infn≥1xn=0 for every x∈(0,1); see [14]. The definition of Archimedean property of t-norms on a bounded poset were proposed by De Baets and Mesiar as follows.
Definition 3.6.[4] A t-norm T on a bounded poset (P,≤) is called Archimedean if for any (x,y)∈P2,
(∀n≥1)(xn≥y)⟹(x=⊤ or y=⊥),
where x1=x and xn+1=T(xn,x) for all n≥1.
Proposition 3.7.[4] A t-norm T on a complete lattice L is Archimedean if and only if
(∀x∈L∖{⊤})(n≥1infxn=⊥),
where x1=x and xn+1=T(xn,x) for all n≥1.
We first establish a property of T1⋆T2 concerning finite suprema.
Lemma 3.8. Let T1 and T2 be t-norms on [0,1]. Then T1⋆T2 preserves finite suprema in each argument. In particular, for all f,g,h∈I, it holds that
Substituting this equivalence into the definition of T1⋆T2 in terms of step functions gives the required equality. Commutativity gives the same conclusion for the second argument. Moreover, T1⋆T2(⊥,h)=⊥, so the empty supremum is also preserved.
Proposition 3.9. Let T1 and T2 be Archimedean t-norms on [0,1]. For each f∈I, define
f1=f,fn+1=T1⋆T2(fn,f)(n≥1).
Then, for every f<⊤, it holds that
n≥1inffn=⊥,(4)
where the infimum is taken in the complete lattice I. If T1⋆T2 is associative, then it is an Archimedean t-norm on I.
Proof. Let f<⊤. There exist r,a∈(0,1) such that f(r)≤a. Set
g=sup{⟨r,1⟩,⟨1,a⟩}.
By the monotonicity of f and the definition of step functions, we have f≤g. Let g1=g and gn+1=T1⋆T2(gn,g) for all n≥1. Also, let r0=a0=1 and define
rn+1=T1(rn,r),an+1=T2(an,a)(n≥0).
Since T1 and T2 are Archimedean, rn⟶0 and an⟶0.
First, we show by induction that
gn=0≤j≤nsup⟨rj,an−j⟩(n≥1).(5)
For n=1, the equality follows from the definition of g. Assume that it holds for some n≥1. By Lemma 3.8 and the formula for T1⋆T2 on step functions, we obtain
If T1⋆T2 is associative, by Proposition 3.1, it is a t-norm on I. Hence, T1⋆T2 is an Archimedean t-norm on I from Proposition 3.7.
Remark 3.10. When T1⋆T2 is associative, the sequence {fn} in Proposition 3.9 consists of the powers of f with respect to T1⋆T2. It should be pointed out that (4) does not imply the stronger condition
∀⊥<f,g<⊤,∃n≥1,fn≤g.
In fact, take T1=T2=TP. Then T1⋆T2 is a t-norm by Theorem 3.4, and both T1 and T2 are Archimedean. Let
f=⟨21,1⟩,g=⟨21,21⟩.
By the formula for T1⋆T2 on step functions, we have
fn=⟨2−n,1⟩(n≥1).
For every n≥1, taking x=2−n−1 gives
fn(x)=1>21=g(x).
Hence fn≰g for all n≥1, even though ⊥<g<f<⊤.
Associativity of the induced operation
This section is devoted to the associativity of the induced operation T1⋆T2. We first prove a general sufficient condition and then examine two complementary examples which show that the condition is meaningful but not necessary.
The proof of the main theorem relies on the following approximation lemma, which allows us to pass from the pointwise formula for T1⋆T2 to the associativity identity.
Lemma 4.1. Let T1 be a continuous t-norm on [0,1]. For all f,g∈I and all x,y∈[0,1] with x<y, there exist ux,vx∈(0,1] such that x<T1(ux,vx) and T2(f(ux),g(vx))≥T1⋆T2(f,g)(y).
Proof. If y=1, then T1⋆T2(f,g)(y)=0, and the conclusion follows by taking ux=vx=1. Henceforth assume y<1.
By Proposition 3.3, set A:=T1⋆T2(f,g)(y)=supy<T1(u,v)T2(f(u),g(v)). Then there is a sequence of pairs (un,vn) with y<T1(un,vn) for all n such that
T2(f(un),g(vn))→A(n→∞).
Since [0,1]2 is compact, after passing to a subsequence if necessary, we may assume that un→u0 and vn→v0. Since y<T1(un,vn)≤min{un,vn} for all n, it follows that u0,v0∈[y,1].
By the continuity of T1,
T1(u0,v0)=n→∞limT1(un,vn)≥y>x.
The continuity of T1 guarantees the existence of a small 0<δ<min{u0,v0} such that
T1(u0−δ,v0−δ)>x.
Set ux:=u0−δ and vx:=v0−δ. For all sufficiently large n, we have un>ux and vn>vx. Because f and g are non-increasing, f(un)≤f(ux) and g(vn)≤g(vx). Since T2 is non-decreasing in each variable,
T2(f(un),g(vn))≤T2(f(ux),g(vx)).
Passing to the limit as n→∞ on the left side yields A≤T2(f(ux),g(vx)), completing the proof.
Theorem 4.2. Suppose that at least one of T1 and T2 is a continuous t-norm on [0,1]. Then T1⋆T2 is a t-norm on I.
Proof. By Proposition 3.1, we need to show that T1⋆T2 is associative. By Proposition 3.2, without loss of generality, we assume that T1 is continuous.
On one hand, take any u,v,w∈[0,1] with x<T1(T1(u,v),w). Because the map T1(−,w) is continuous and x<T1(T1(u,v),w), there exists some r∈[0,1] such that
and note that ⟨TD(u,v),TD(a,b)⟩=⟨0,0⟩ iff both TD(u,v)=0 and TD(a,b)=0.
(i) If u=1, then ⟨1,a⟩≤f implies a≤f(1−)<1. From TD(a,b)=0 we obtain b=1. The condition ⟨v,b⟩≤g implies ⟨b,v⟩≤g∗, and hence v≤g∗(b)=g∗(1−). Consequently,
⟨TD(u,v),TD(a,b)⟩=⟨v,a⟩≤⟨g∗(1−),f(1−)⟩.
(ii) If v=1, a symmetric argument yields
⟨TD(u,v),TD(a,b)⟩≤⟨f∗(1−),g(1−)⟩.
Therefore,
TD⋆TD(f,g)≤sup{⟨f∗(1−),g(1−)⟩,⟨g∗(1−),f(1−)⟩}.
Now, we prove the reverse inequality. By Lemma 2.5(1), ⟨1,f∗(1−)⟩≤f∗ and ⟨1,g(1−)⟩≤g. Besides, ⟨1,f∗(1−)⟩≤f∗ implies ⟨f∗(1−),1⟩≤f. Hence,
The following example shows that T1⋆T2 need not be associative when neither component t-norm is continuous.
Example 4.4. Neither the t-norm TD nor TnM is continuous, although TnM is left-continuous. We show that the operation TD⋆TnM is not associative.
Given any a,b∈(0,1) with a<b, let f:[0,1]⟶[0,1] and h:[0,1]⟶[0,1] be two strictly decreasing maps that are continuous on [0,1), f(0)=h(0)=1, f(1−)=h(1−)=0.1, f(1)=h(1)=0, and f(a)=h(b)=0.9. Let the map g:[0,1]⟶[0,1] be given by
g(x)={0.9,0,x∈[0,1),x=1.
Clearly, f,g,h∈I. We show that
TD⋆TnM(TD⋆TnM(f,g),h)=TD⋆TnM(f,TD⋆TnM(g,h)).
Note that x<TD(u,v) if and only if u=1,v>x or v=1,u>x. Hence for all λ,μ∈I,
We have shown that for any two t-norms T1,T2 on [0,1], the operation T1⋆T2 defined on the fuzzy unit interval I is always commutative, monotone and has ⟨1,1⟩ as its neutral element. Associativity—and hence the property of being a t-norm—holds in the following cases:
At least one of T1,T2 is continuous.
Both T1 and T2 are left-continuous; in this case T1⋆T2 is precisely the tensor product of the quantales ([0,1],T1) and ([0,1],T2).
The example TD⋆TD shows that neither continuity nor left-continuity is necessary. On the other hand, the case of TD⋆TnM shows failure of associativity, showing that the interaction between a left-continuous t-norm and a non-left-continuous t-norm can destroy associativity. For the reader’s convenience, we summarize the known cases established or recalled in this paper in the following table.
T1
T2
Is T1⋆T2 a t-norm?
left-continuous
left-continuous
yes
continuous
arbitrary
yes
arbitrary
continuous
yes
TD
TD
yes
TD
TnM
no
Table 1.
The case of two left-continuous components belongs to the existing quantale tensor-product theory. The new associativity result permits one component to be arbitrary when the other is continuous; the drastic pair shows that even two components failing left-continuity may work. The contrasting example shows why these results do not extend to arbitrary pairs.
The Archimedean discussion in § 3 answers a separate question: two Archimedean components imply that the fixed recursive powers of each f<⊤ have infimum ⊥ in I. If the induced operation is associative, this gives an Archimedean t-norm.
However, a complete characterization of those pairs (T1,T2) for which T1⋆T2 is a t-norm remains an open problem.
Acknowledgements
Rongjun Wu would like to express gratitude to the Southwest Minzu University Research Startup Funds for Grant (#RQD2021100), which supported the writing of this article. Jie Sun would like to express gratitude to the National Natural Science Foundation of China (No. 12601905) and the Southwest Minzu University Research Startup Funds for Grant (#RQD2024011). Hongliang Lai would like to express gratitude to the National Natural Science Foundation of China (No. 12671089).
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