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Research Article

Graded fuzzy topological spaces

| (Reviewing Editor)
Article: 1138574 | Received 13 Aug 2015, Accepted 01 Jan 2016, Published online: 10 Feb 2016

Abstract

In this paper, graded fuzzy topological spaces based on the notion of neighbourhood system of graded fuzzy neighbourhoods at ordinary points are introduced and studied. These graded fuzzy neighbourhoods at ordinary points and usual subsets played the main role in this study.

AMS Subject Classifications:

Public Interest Statement

Separation axioms depend on the concept of neighbourhoods and so, for the fuzzy case, fuzzy neighbourhoods or valued fuzzy neighbourhoods means neighbourhoods with some degree in [0, 1] . These grades to be a fuzzy neighbourhood forced the fuzzy separation axioms to be graded. In the fuzzy case, separation axioms are not sharp concepts. For example, there is no T0 topological space, but there are (α,β)-T0 topological spaces depending on the existence of the fuzzy neighbourhood with grade α at a point or the existence of the fuzzy neighbourhood with grade β at the other distinct point. In this paper, I introduced these graded fuzzy separation axioms. The main section was for defining a fuzzy neighbourhood system of fuzzy graded neighbourhoods at ordinary points and usual subsets.

1. Introduction

Kubiak (Citation1985) and Sǒstak (Citation1985) introduced the fundamental concept of a fuzzy topological structure as an extension of both crisp topology and fuzzy topology Chang (Citation1968), in the sense that both objects and axioms are fuzzified and we may say they began the graded fuzzy topology. Bayoumi and Ibedou (Citation2001,Citation2002,Citation2002b,Citation2004) introduced and studied the separation axioms in the fuzzy case in Chang’s topology (Citation1968) using the notion of fuzzy filter defined by Gähler (Citation1995a,Citation1995b).

Now, we will try to investigate fuzzy topological spaces in sense of Soˇstak, not using fuzzy filters but starting from a neighbourhood system of graded fuzzy neighbourhoods at ordinary points and usual sets. From that neighbourhood system, we can build a fuzzy topology in sense of Soˇstak and moreover, this fuzzy topology is itself the fuzzy topology in sense of Chang associated with the fuzzy neighbourhoterest Satementod filter Nx (Gähler, Citation1995b) at ordinary point xX defined by Gähler. Interior operator and closure operator are defined using these graded fuzzy neighbourhoods; also their associated fuzzy topologies coincide with this fuzzy topology in sense of Chang associated with the fuzzy neighbourhood filter of Gähler. Fuzzy continuous, fuzzy open and fuzzy closed mappings are defined with grades according to these graded fuzzy neighbourhoods.

Separation axioms in the fuzzy case are introduced based on these graded fuzzy neighbourhoods and thus, axioms are graded. These axioms satisfy common results and implications. These graded axioms are a good extension in sense of Lowen (Citation1978). In Fuzzy neuro systems for machine learning for large data sets (Citation2009) and DCPE Co-Training for Classification (Citation2012), there are some applications based on fuzzy sets.

2. Preliminaries

Throughout the paper, let I0=(0,1] and I1=[0,1).

A fuzzy topology τ:IXI is defined by Kubiak (Citation1985) and Sǒstak (Citation1985):

(1)

τ(0¯)=τ(1¯)=1,

(2)

τ(fg)τ(f)τ(g) for all f,gIX,

(3)

τ(jJμj)jJτ(μj) for any family of (μj)jJIX.

Let τ1 and τ2 be fuzzy topologies on X. Then, τ1 is finer than τ2 (τ2, which is coarser than τ1), denoted by τ1τ2, if τ2(μ)τ1(μ) for all μIX.

For each fuzzy set fIX, the weak α cut-off f is given by wαf={xXf(x)α}; the strong α cut-off f is the subset of X, sαf={xXf(x)>α}.

If T is an ordinary topology on X, then the induced fuzzy topology on X is given by ω(T)={fIXsαfTfor allαI1}.

fuzzy filters. Let X be a non- empty set. A fuzzy filter on X (Eklund, Citation1992; Gähler, Citation1995a) is a mapping M:IXI such that the following conditions are fulfilled:

(F1)

M(α¯)α holds for all αI and M(1¯)=1;

(F2)

M(fg)=M(f)M(g) for all f,gIX.

If M and N are fuzzy filters on X, then M is said to be finer than N, denoted by MN, provided that M(f)N(f) for every fIX. By MN we mean that M is not finer than N. MNthere isfIXsuch thatM(f)<N(f).

A non-empty subset F of IX is called a prefilter on X (Lowen, Lowen), provided that the following conditions are fulfilled:

(1)

0¯F;

(2)

f,gF implies fgF;

(3)

fF and fg imply gF.

For each fuzzy filter M on X, the subset α-prM of IX defined by:α-prM={fIXM(f)α}

is a prefilter on X.

Proposition 2.1

(Gähler, Citation1995a) There is a one-to-one correspondence between fuzzy filters M on X and the families (Mα)αI0 of prefilters on X which fulfill the following conditions:

(1)

fMα implies αsupf.

(2)

0<αβ implies MαMβ.

(3)

For each αI0 with 0<β<αβ=α, we have 0<β<αMβ=Mα.

This correspondence is given by Mα=α-pr M for all αI0 and M(f)=gMα,gfα for all fIX.

Proposition 2.2

(Eklund, Citation1992) Let A be a set of fuzzy filters on X. Then, the following are equivalent.

(1)

The infimum MAM of A with respect to the finer relation of fuzzy filters exists,

(2)

For each non-empty finite subset {M1,,Mn} of A, we have M1(f1)Mn(fn)sup(f1fn) for all f1,,fnIX,

(3)

For each αI0 and each non-empty finite subset f1,,fn of MAα-prM, we have αsup(f1fn).

Recall that (MAM)(f)=MAM(f) and (MAM)(f)=MAM(f) for all fIX.

Fuzzy neighbourhood filters. For each fuzzy topological space (X,τ) and each xX, the mapping Nx:IXI defined by (Gähler, Gahler):Nx(λ)=intτλ(x)for allλIX

is a fuzzy filter on X, called the fuzzy neighbourhood filter of the space (X,τ) at the point x, and for short is called a fuzzy neighbourhood filter at x. The mapping x˙:IXI is defined by x˙(λ)=λ(x) for all λIX. The fuzzy neighbourhood filters fulfil the following conditions:

(1)

x˙Nx holds for all xX;

(2)

(Nx)(intτf)=(Nx)(f) for all xX and fIX.

A fuzzy filter M is said to converge to xX, denoted by Mx, if MNx (Gähler, Citation1995b).

The fuzzy neighbourhood filter NF at an ordinary subset F of X is the fuzzy filter on X defined in Bayoumi and Ibedou (Citation2002b), by means of Nx, xF as:NF=xFNx.

The fuzzy filter F˙ is defined byF˙=xFx˙.F˙NF holds for all FX. Also, recall that the fuzzy filter λ˙ and the fuzzy neighbourhood filter Nλ at a fuzzy subset λ of X are defined by(1) λ˙=0<λ(x)x˙andNλ=0<λ(x)Nx,(1)

respectively. λ˙Nλ holds for all λIX (Bayoumi & Ibedou, Citation2004).

For each fuzzy topological space (X,τ) the closure operator cl which assigns to each fuzzy filter M on X, the fuzzy filter clM is defined by(2) clM(f)=clτgfM(g).(2) clM is called the closure of M. cl is isotone, hull and idempotent operator, that is for all fuzzy filters M and N on X, we have (Gähler, Citation1995b):(3) MNimpliesclMclN,(3) (4) MclM,(4)

3. Neighbourhood systems

Definition 3.1

A family (Nxα)xX of fuzzy sets Nxα is said to be a neighbourhood system with grade αI0 on X if it satisfies the following conditions:

(Nb1)

For all fNxα, we have αf(x),

(Nb2)

1¯Nxα,

(Nb3)

f,gNxα implies that fgNxα,

(Nb4)

fNxα, fg imply that gNxα,

(Nb5)

If fNxα, then there is gNxα, such that for all yX with 0<g(y), we have fNyα.

Lemma 3.2

These families of prefilters (Nxα)αI0 at xX satisfy the following conditions:

(Pr1)

fNxα implies that αsupf,

(Pr2)

0<βα implies that NxαNxβ,

(Pr3)

For every αI0 with 0<β<αβ=α, we have 0<β<αNxβ=Nxα.

Proof

Clear.

Remark 3.3

For any subset A of X, let us define NAα by NAα=xANxα, that is fNAα iff αxANx(f) iff αNA(f). Nxα=N{x}α, NxαNxβ=Nxαβ, NxαNxβ=Nxαβ, jNxαj=Nxjαj, jNxαj=Nxjαj. For all αβ in I0, we have NxαNxβ.

For any α,β,γI0, we have NxαNxα, NxαNxβ and NxβNxα implies that α=β, NxαNxβ and NxβNxγ implies that NxαNxγ. Also, for all αβI0, we have either NxαNxβ or NxβNxα.

(α) fuzzy open sets, fuzzy open sets.

Let us define an (α) fuzzy open set as follows:(5) ατ(f)iffforallxXthereisαI0suchthatfNxαandf(x)α.(5)

An (α) fuzzy closed set is the complement of an (α) fuzzy open set.

A set fIX is said to be fuzzy open if it is (α) fuzzy open for all αI0. In other words, if for all xX and for all αI0, we have fNxα and f(x)α.

It is called a fuzzy closed if it is the complement of a fuzzy open set. These notations are restricted to the usual open and closed sets in fuzzy topology and usual topology.

Starting from a neighbourhood system (Nxα)xX with grade αI0, we can define an interior operator and a closure operator as follows:(6) intf(x)=gNxα0<g(y)f(y),(6) (7) clf(x)=gNxα0<g(y)f(y).(7) For every xX, Nxα satisfying (Nb1) to (Nb4) is exactly a prefilter on X of all neighbourhoods of xX with grade αI0. That is, (Nxα)xX is a family of prefilters with grade αI0 at every xX constructing after adding condition (Nb5) a neighbourhood system on X with grade αI0. The pair (X,(Nxα)xX) is called a neighbourhood space with a grade αI0.

From Lemma 2.1 and from the correspondence given in Proposition 2.1 between the fuzzy filters and the families satisfying the conditions (Pr1) to (Pr3), we can say this family (Nxα)αI0 is a representation of the fuzzy neighbourhood filter Nx as a family of prefilters. This is given by the following two conditions (Nb) and (Pr):

(Pr)

Nx(f)=gNxα,gfα for all fIX.

(Nb)

Nxα={fIXαNx(f)}.

Denote the subset NxαIX as the fuzzy neighbourhoods with grade αI0 of xX.

Clearly, both the interior operator and closure operator satisfy the common axioms of interior operator and closure operator, respectively. A fuzzy topology on X could be generated by this interior operator given by (2.2) or this closure operator given by (2.3), using the properties of Nxα stated in (Nb1)—(Nb5). That fuzzy topology is exactly the fuzzy topology τ associated with the fuzzy neighbourhood filters Nx given by an interior operation as in (2.2) so thatNx(f)=intτf(x)forallfIX.

Also, we can consider(8) Nxα={fIXαintτf(x)}(8)

and then, (2.1) for an (α) fuzzy open set could be rewritten as(9) ατ(f)iffforallxX,thereisαI0sothatαintτf(x),f(x)α.(9)

That is, from a neighbourhood system of graded neighbourhoods, we can deduce interior operation by which it is introduced a graded fuzzy topology and the converse is true.

From (1.2) and (1.4) for all xX and all αI0, we can define clNxα by(10) clNxα={fIXαclNx(f)},(10)

and equivalently,(11) clNxα={fIXthereishNxα,clhf}.(11)

For all xX and all αI0, we have clNxαNxα.

Definition 3.4

Let (X,τ1) and (Y,τ2) be fuzzy topological spaces, and f:XY a map. Then, for some αI0, f is called (α) fuzzy continuous if for all (α) fuzzy open set μ with respect to τ2, we have f-1(μ) is an (α) fuzzy open set with respect to τ1 for all μIY.

f is called fuzzy continuous if for all fuzzy open set μ with respect to τ2, we have f-1(μ) is a fuzzy open set with respect to τ1 for all μIY.

Definition 3.5

Let (X,τ1) and (Y,τ2) be fuzzy topological spaces. Then, the mapping f:(X,τ1)(Y,τ2) is called (α) fuzzy open ((α) fuzzy closed) mapping if the image f(g) of the (α) fuzzy open ((α) fuzzy closed) set g with respect to τ1 is (α) fuzzy open ((α) fuzzy closed) set with respect to τ2.

The mapping f:(X,τ1)(Y,τ2) is called fuzzy open (fuzzy closed) mapping if the image f(g) of the fuzzy open (fuzzy closed) set g with respect to τ1 is fuzzy open (fuzzy closed) set with respect to τ2.

Now, we define the continuity locally at a point x0X between two fuzzy topological spaces using these graded neighbourhoods.

Definition 3.6

Let (X,τ) and (Y,σ) be two fuzzy topological spaces. Then, the mapping f:(X,τ)(Y,σ) is called (α) fuzzy continuous at a point x0   provided that for all gNf(x0)α,

there exists hNx0α such that hf-1(g) for some αI0. f is (α) fuzzy continuous if it is (α) fuzzy continuous at every xX. f is an fuzzy continuous if it is (α) fuzzy continuous for all αI0.

This is an equivalent definition with Definition 2.2 for the (α) fuzzy continuous mapping and fuzzy continuous mapping.

4. (α,β)T0-spaces and (α,β)T1-spaces

This section is devoted to introduce the notions of T0-spaces and T1-spaces using the notion of α-neighbourhoods at ordinary points. We will introduce different equivalent definitions,

and we show that these notions are good extensions in sense of Lowen (Citation1978]).

Definition 4.1

A fuzzy topological space (X,τ) is called an (α,β)T0-space if for all xy in X, there exists fNxα such that f(y)<α; αI0 or there exists gNyβ such that g(x)<β; βI0.

Definition 4.2

A fuzzy topological space (X,τ) is called an (α,β)T1-space if for all xy in X there exist fNxα and gNyβ such that f(y)<α and g(x)<β; α,βI0.

Example 4.3

Let X={x,y}, and τ(f)=1at0¯or1¯13atx120otherwise.Taking α=13, we get that there is f=x12 in Nxα such that f(y)<α. For all αI0, we can not find any f in Nyα such that f(x)<α. That is, (X,τ) is an (α,β)T0-space.

Example 4.4

Let X={x,y}, andτ(f)=1at0¯or1¯0otherwise.

Only there is f=1¯ which is a graded neighbourhood but for both of xy. Hence, for all αI0, Nxα=Nyα and therefore, (X,τ) is not (α,β)T0-space.

Proposition 4.5

Every (α,β)T1-space is an (α,β)T0-space.

Proof

Clear.

Example 3.1 is an (α,β)T0-space but not (α,β)T1-space.

Example 4.6

Let X={x,y}, and τ(f)=1at0¯or1¯13atx1213aty120otherwise.Taking α=13 and β=13, we get that there is f=x12 in Nxα and g=y12 in Nyβ such that f(y)<α and g(x)<β, for some α,βI0. Hence, (X,τ) is an (α,β)T1-space.

In the following theorems, there will be introduced some equivalent definitions for the (α,β)T0-spaces and (α,β)T1-spaces.

Theorem 4.7

Let (X,τ) be a fuzzy topological space. Then, the following statements are equivalent.

(1)

(X,τ) is (α,β)T0.

(2)

For all xy in X and for all αI0, NxαNyα.

(3)

For all xy in X, there exists fIX such that f(y)<αintτf(x); αI0 or there exists gIX such that g(x)<βintτg(y); βI0.

(4)

For all xy in X, there exists fIX such that f(y)<clτf(x) or there exists gIX such that g(x)<clτg(y).

Proof

(1)(2): From (1), there is fIX such that intτf(y)f(y)<αintτf(x); αI0 and then, fNxα and fNyα. Hence, NxαNyα; αI0 and thus, (2) holds.

(2)(3): There exists fIX such that intτf(y)<αintτf(x); αI0 and then, for g=intτf, we can say g(y)<αintτg(x); αI0. The other case is similar and thus, (3) is satisfied.

(3)(4): From Equation 2.3, we get that clτf)(x)f(y) whenever intτf(y)αf(x), then (4) holds.

(4)(1): Since f(y)<hNxα0<h(z)f(z)=clτf(x) implies that z could not be y with 0<h(y) for all hNxα; αI0, which means that there is hNxα such that h(y)=0<αintτh(x); αI0. The other case is similar and thus, (1) holds.

Theorem 4.8

Let (X,τ) be a fuzzy topological space. Then, the following statements are equivalent.

(1)

(X,τ) is (α,β)T1.

(2)

For all xX, we have clτx1=x1.

(3)

For all xy in X, there exist f,gIX such that f(y)<αintτf(x) and g(x)<βintτg(y); α,βI0.

(4)

For all xy in X, there exist f,gIX such that f(y)<clτf(x) and g(x)<clτg(y).

Proof

(1)(2): Let yx in X. Then, clτx1(y)=hNyα0<h(z)x1(z), which means for all hNyα, if x1(z)>0 whenever h(z)>0, then clτx1(y)>0. From (1), we get that z could not be x with 0<h(x), that is, clτx1(y)=0 for all yx. At x, it is clear that clτx1(x)=1. Hence, clτx1=x1 for all xX, and (2) is fulfilled.

(2)(3): For all xy in X, we have clτx1=x1 and clτy1=y1. (2) means that clτx1(y)=x1(y)=0=hNyα0<h(z)x1(z), which means for all hNyα, z could not be x with 0<h(x), that is there is αI0 and there is hNyα such that h(x)=0<α and then, h(x)<αintτh(y). The other case is similar and therefore, (3) is fulfilled.

(3)(4): As in Theorem 4.1.

(4)(1): As in Theorem 4.1.

The next proposition shows that the separation axioms (α,β)T0 and (α,β)T1 are good extensions in sense of Lowen (Citation1978).

Proposition 4.9

A topological space (XT) is a T0-space (T1-space) if and only if the induced fuzzy topological space (X,ω(T)) is an (α,β)T0-space ((α,β)T1-space).

Proof

Let (XT) be T0 (T1) and let xy. Then, there is a neighbourhood OyT such that xOy. Taking fIX such that Oy=sαfT for some αI1, we get f(x)α<intω(T)f(y), That is, f(x)<αintω(T)f(y) for some αI0. Similarly, if there is a neighbourhood OxT such that yOx, we can find gIX such that Ox=sβgT and g(y)β<intω(T)g(x) for some βI1, That is, g(y)<βintω(T)g(x) for some βI0. Hence, (X,ω(T)) is an (α,β)T0-space ((α,β)T1).

Conversely, let (X,ω(T)) be an (α,β)T0-space ((α,β)T1) and xy. Then, there exists fIX such that f(y)<αintω(T)f(x) for some αI0, which means f(y)α<intω(T)f(x) for some αI1, that is there is intω(T)fIX such that sαintω(T)f=OxT and yOx. Similarly, the other case is proved. Hence, (XT) is a T0-space (T1).

Proposition 4.10

Let (X,τ) be an (α,β)T0-space ((α,β)T1) and let σ be a fuzzy topology on X finer than τ. Then, (X,σ) is also (α,β)T0-space ((α,β)T1-space).

Proof

(X,τ) is an (α,β)T0-space ((α,β)T1) implying that there is fIX such that αintτf(x) and f(x)<α or (and) there is gIX such that αintτg(x) and g(x)<α, which implies that ατ(f) or (and)ατ(g). Since σ is finer than τ, then ασ(f) or (and)ασ(g), and thus, αintσf(x) and f(x)<α or (and) αintσg(x) and g(x)<α. Hence (X,σ) is an (α,β)T0-space ((α,β)T1).

5. (α,β)T2-spaces

Here, we introduce and study the Hausdorff separation axiom in fuzzy topological spaces.

Definition 4.11

An fuzzy topological space (X,τ) is called an (α,β)T2-space if for all xy in X there exist fNxα and gNyβ such that (αβ)>sup(fg); α,βI0.

Proposition 4.12

Every (α,β)T2-space is an (α,β)T1-space.

Proof

Let (X,τ) be an (α,β)T2-space but not (α,β)T1-space. That is, for xy, we get for all fNxα that f(y)α for all αI0. Since for any gNyβ we have g(y)β, then (fg)(y)=f(y)g(y)(αβ) and thus, sup(fg)(αβ) which contradicts the axiom (α,β)T2. Hence, (X,τ) is an (α,β)T1-space.

Example 4.13

Let X={x,y}, and τ(f)=1at0¯or1¯15atx145atx13y10otherwise.There are f=x1IX and g=x13y1IX such that, for α=15 and β=45 in I0, we get that f=x1Nxα and g=x13y1Nyβ such that f(y)=x1(y)=0<15=α and g(x)=(x13y1)(x)=13<45=β. That is, (X,τ) is an (α,β)T1-space. But for all fuzzy sets fNxα and gNyβ, we get that (αβ)sup(fg) and thus, (X,τ) is not (α,β)T2-space.

Theorem 4.14

Let (X,τ) be an fuzzy topological space. Then, the following statements are equivalent.

(1)

(X,τ) is (α,β)T2.

(2)

For all fuzzy ultrafilter M on X and for all xy, there is fNxα such that M(f)<α; αI0 or there is gNyβ such that M(g)<β; βI0.

(3)

For all fuzzy filter M on X and for all xy, there is fNxα such that M(f)<α; αI0 or there is gNyβ such that M(g)<β; βI0.

Proof

(1)(2): Suppose that there is an fuzzy ultrafilter M on X such that M(f)α and M(g)β for all fNxα and gNyβ. That is, M(fg)=M(f)M(g)αβ, but in common we know that M(h)suph for all hIX, which means that for all fNxα and gNyα, we have sup(fg)(αβ) and therefore, (1) implies (2) is satisfied.

(2)(3): Since for any fuzzy filter M on X we find a finer fuzzy ultrafilter I on X, that is M(f)I(f) for all fIX, then (2) implies that there is fNxα such that M(f)I(f)<α; αI0 or there is gNyβ such that M(g)I(g)<β; βI0. Thus, (3) holds.

(3)(1): Suppose for all fNxα and gNyβ; α,βI0 that (αβ)sup(fg) and (3) is fulfilled. Then, for all fuzzy filter M on X, we have M(f)<α or M(g)<β; α,βI0. Hence, M(fg)<(αβ)sup(fg), which means a contradiction to the common result that M(fg)sup(fg) and therefore, M(fg)sup(fg)<(αβ). Thus, (1) is satisfied.

Example 4.15

Let X={x,y}, and τ(f)=1at0¯or1¯14atx1314aty130otherwise.There are f=x13IX and g=y13IX such that for α=14 and β=14 in I0, we get that f=x13 in Nxα and g=y13 in Nyβ such that (αβ)=14>sup(x13y13)=0 and thus, (X,τ) is an (α,β)T2-space.

Proposition 4.16

A topological space (XT) is a T2-space if and only if the induced fuzzy topological space (X,ω(T)) is an (α,β)T2-space.

Proof

Let xy in X. Then, there are Ox,OyT such that OxOy=. Taking f,gIX such that sαf=Ox,sβg=Oy for some α,βI1, then intω(T)f(x)>α and intω(T)g(y)>β; α,βI1, that is intω(T)f(x)α and intω(T)g(y)β; α,βI0 and then, fNxα and gNyβ such that sαfsβg=OxOy=, which means that there is no element zX such that (fg)(z)=f(z)g(z)intω(T)f(z)intω(T)g(z)>(αβ); α,βI1, which means for all zX, we have (fg)(z)(αβ); α,βI1. Hence, sup(fg)(αβ); α,βI1 and then, sup(fg)<(αβ); α,βI0 and thus, (X,ω(T)) is an (α,β)T2-space.

Conversely, xy implies that there are fNxα and gNyβ such that intω(T)f(x)intω(T)g(y)(αβ)>sup(fg); α,βI0. That is, for γ=sup(fg)I1, we can say intω(T)fω(T),xsγintω(T)f and intω(T)gω(T),ysγintω(T)g, which means that sγintω(T)f=OxT, sγintω(T)g=OyT and moreover, OxOy= and thus, (XT) is a T2-space. (because if there is z(OxOy), then (fg)(z)intω(T)f(z)intω(T)g(z)>γ=sup(fg) which is a contradiction).

Proposition 4.17

Let (X,τ) be an (α,β)T2-space, and let σ be an fuzzy topology on X finer than τ. Then, (X,σ) is also an (α,β)T2-space.

Proof

Let xyX. Then, there are fNxα and gNyβ such that (αβ)>sup(fg); α,βI0, that is αintτf(x), βintτg(y) and (αβ)>sup(fg), which means that αintσf(x), βintσg(y) and (αβ)>sup(fg); α,βI0 and thus, fNxα and gNyβ in (X,σ) such that (αβ)>sup(fg); α,βI0. Hence, (X,σ) is an (α,β)T2-space.

6. (α,β)T3-spaces and (α,β)T4-spaces

In this section, we use fuzzy neighbourhood filters at ordinary sets to define the notions of (α,β)T3-spaces and (α,β)T4-spaces.

Definition 5.1

A fuzzy topological space (X,τ) is called (α,β) regular if for all F=clτF in P(X) and xF, there exist fNxα and gNFβ such that (αβ)>sup(fg); α,βI0.

Definition 5.2

A fuzzy topological space (X,τ) is called (α,β)T3-space if it is regular and (α,β)T1.

Definition 5.3

A fuzzy topological space (X,τ) is called normal if for all F1=clτF1,F2=clτF2P(X) with F1F2=, there exist fNF1α and gNF2β such that (αβ)>sup(fg); αβI0.

Definition 5.4

A fuzzy topological space (X,τ) is called (α,β)T4 if it is normal and (α,β)T1.

Proposition 5.5

Every (α,β)T3-space is an (α,β)T2-space.

Proof

Let xy in X. (X,τ) is an (α,β)T1-space meaning that clτ{x}={x} for each xX. Now, clτ{y}={y}, x{y}, and (X,τ) is regular implying that there are fNxα,gNyβ such that (αβ)>sup(fg); α,βI0. Hence, (X,τ) is an (α,β)T2-space.

Theorem 5.6

For each fuzzy topological space (X,τ), the following are equivalent.

(1)

(X,τ) is regular.

(2)

For all yF=clτF and xF, we have NxαclNyα and NyβclNxβ for all yF; α,βI0.

(3)

For all xX and all αI0, we have clNxα=Nxα.

(4)

For all xX, for all fuzzy filter M on X, for all fNxα, and for all αI0, we have M(f)α implies clM(f)α.

Proof

(1)(2): Let fNxα; αI0. Suppose that fclNyα for some yF, that is, there is hNyα with clτhf, which means that f(y)α. Since for all gNyα, we have g(y)α for all yF; αI0, then sup(fg)(fg)(y)α=(αα) for some fNxα for all xF, and for all gNyα for some yF; αI0, which contradicts (1) and therefore, fclNyα for all yF. Thus, NxαclNyα for all yF. The other case is similar and hence, (2) is satisfied.

(2)(3): From (2) we deduce that for all fNxαandgNyβ, we have fclNyαorgclNxβ for all α,βI0 implies x=y. Hence, for all fNxα, xX, and all αI0, we get that fclNxα, which means that NxαclNxα, but from that clNxαNxα for all αI0 and for all xX, we get that clNxα=Nxα for all αI0 and for all xX and thus, (3) holds.

(3)(4): Let M be a fuzzy filter on X with M(f)α for all fNxα and αI0. From (3), M(f)α for all fclNxα and αI0 and then, clM(f)α for all fNxα and αI0 and thus, (4) is fulfilled.

(4)(1): Consider M=Nx in (4), we get that clNxα=Nxα for all xX and all αI0. Now, for yF=clτF and xy, we get for all fNxαandgNyβ that fclNxαandgclNyβ, which means there are hNxαwithclτhf and kNyβwithclτkg. Choose f=clτχFcNx1 and g=clτ(intτχF)NF1, then we can find h=χFcNx1 and k=intτχFNF1 such that (αβ)=1>0=sup(χFcintτχF)=sup(hk), and thus, for all F=clτFX a nd xF, there exist hNxα and kNFβ such that (αβ)>sup(hk); α,βI0, and therefore, (1) is satisfied.

Theorem 5.7

Let (X,τ) be a fuzzy topological space. Then, the following are equivalent.

(1)

(X,τ) is normal.

(2)

For all F1=clτF1,F2=clτF2P(X) with F1F2=, we have NxαclNyα and NyβclNxβ for all xF1andyF2; α,βI0.

(3)

For all F=clτFP(X), and all αI0, we have clNFα=NFα.

(4)

For all F=clτFP(X), for all fuzzy filters M on X, for all fNFα, and for all αI0, we have M(f)α implies clM(f)α.

Proof

Similar to the Theorem 6.1.

Proposition 5.8

Every (α,β)T4-space is an (α,β)T3-space.

Proof

Let xF=clτF in X. Since (X,τ) is (α,β)T4, then it is (α,β)T1, which means that clτ{x}={x} for all xX, which implies that we have F1={x}=clτ{x} and F2=F with F1F2=. Hence, there are fNxα and gNFβ such that (αβ)>sup(fg); α,βI0 and thus, (X,τ) is regular and it is (α,β)T1. Therefore, (X,τ) is (α,β)T3.

Example 5.9

Let X={x,y}, and τ(f)=1at0¯or1¯12atx113aty120otherwise.We notice that {y} is a closed set and x{y}. Then, there are f=x1IX and g=y12IX such that for α=12 and β=13 in I0, we get that f=x1 in Nxα and g=y12 in N{y}β such that (αβ)=13>sup(x1y12)=0 and thus, (X,τ) is an (α,β) regular space. Also, it is an (α,β)T1-space. Hence, (X,τ) is an (α,β)T3-space

Example 6.2

Let X={x,y}, and τ(f)=1at0¯or1¯12atx112aty10otherwise.We see that {x} and {y} are disjoint closed subsets of X. Then, there are f=x1IX and g=y1IX such that for α=12 and β=12 in I0, we get that f=x1 in N{x}α and g=y1 in N{y}β such that (αβ)=12>sup(x1y1)=0 and thus, (X,τ) is an (α,β) normal space. Also, it is an (α,β)T1-space. Hence, (X,τ) is an (α,β)T4-space

Proposition 5.11

A topological space (XT) is T3 if and only if the induced fuzzy topological space (X,ω(T)) is (α,β)T3.

Proof

(XT) is T1 iff (X,ω(T)) is (α,β)T1 is proved in Proposition 4.2.

Let F=clτF and xF in X. Then, there are Ox,OFT such that OxOF=. Taking f=χFcandg=χOF in ω(T), we get that intω(T)f(x)intω(T)g(F)=1>0=sup(fg). Hence, there are Nx1 and NF1 of x and F respectively, such that 1>sup(fg) and thus, (X,ω(T)) is an (α,β)T3-space.

Conversely, F=clτF and xF imply there are fNxα and gNyβ for all yF such that intω(T)f(x)intω(T)g(F)(αβ)>sup(fg); αβI0. That is, intω(T)fω(T),xsαintω(T)f and intω(T)gω(T),Fsβintω(T)g, which means that sαintω(T)f=OxT, sβintω(T)g=OFT and moreover, OxOF=, and thus, (XT) is a T3-space.

Proposition 5.12

A topological space (XT) is T4 iff the induced fuzzy topological space (X,ω(T)) is an (α,β)T4.

Proof

Similar to Proposition 6.3.

Proposition 6.5

Let (X,τ) be an (α,β)T3-space, and let σ be an fuzzy topology on X finer than τ. Then, (X,σ) is also an (α,β)T3-space.

Proof

Let xX and F be a closed subset of X with xF. Then, there are fNxα and gNFβ such that (αβ)>sup(fg); α,βI0, that is αintτf(x), βintτg(y) for all yF and (αβ)>sup(fg), which means that αintσf(x), βintσg(y) for all yF and (αβ)>sup(fg); α,βI0 and thus, fNxα and gNFβ in (X,σ) such that (αβ)>sup(fg); α,βI0. Hence, (X,σ) is an (α,β) regular space. Proposition 4.3 states that (X,σ) is an (α,β)T1-space, and thus, it is an (α,β)T3-space.

Proposition 6.6

Let (X,τ) be an (α,β)T4-space and let σ be a fuzzy topology on X finer than τ. Then, (X,σ) is also an (α,β)T4-space.

Proof

Similar to the proof in Proposition 6.5.

Additional information

Funding

The author received no direct funding for this research.

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