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PROBABILISTIC METRIC SPACES. PART II

DOREL MIHET¸

Received 7 June 2004 and in revised form 3 December 2004

A fixed point theorem concerning probabilistic contractions satisfying an implicit rela- tion, which generalizes a well-known result of Hadˇzi´c, is proved.

1. Preliminaries

In this section we recall some useful facts from the probabilistic metric spaces theory. For more details concerning this problematic we refer the reader to the books [1,3,9].

1.1.t-norms. Atriangular norm(shortlyt-norm) is a binary operationT: [0, 1]×[0, 1] [0, 1] :=I which is commutative, associative, monotone in each place, and has 1 as the unit element.

Basic examples areTL:I×II,TL(a,b)=Max(a+b1, 0) (Łukasiewiczt-norm), TP(a,b)=ab, andTM(a,b)=Min{a,b}. We also mention the following families oft- norms:

(i)Sugeno-Weber family(TλSW)λ(1,), defined byTλSW=max(0, (x+y1 +λxy)/

(1 +λ)),

(ii)Domby family (TλD)λ(0,), defined by TλD =(1 + (((1x)/x)λ+ ((1 y)/

y)λ)1/λ)1,

(iii)Aczel-Alsina family(TλAA)λ(0,), defined byTλAA=e(|logx|λ+|logy|λ)1/λ.

Definition 1.1[2,3]. It is said that thet-normTisof Hadˇzi´c-type(H-typefor short) and TᏴif the family{Tn}nNof its iterates defined, for eachxin [0, 1], by

T0(x)=1, Tn+1(x)=TTn(x),x, n0, (1.1) is equicontinuous atx=1, that is,

ε(0, 1)δ(0, 1) such thatx >1δ=⇒Tn(x)>1ε, n1. (1.2) There is a nice characterization of continuoust-norms Tof the classᏴ[8].

Copyright©2005 Hindawi Publishing Corporation

International Journal of Mathematics and Mathematical Sciences 2005:5 (2005) 729–736 DOI:10.1155/IJMMS.2005.729

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(i) If there exists a strictly increasing sequence (bn)nNin [0, 1] such that limn→∞bn= 1 andT(bn,bn)=bnnN, thenTis of Hadˇzi´c-type.

(ii) IfTis continuous andTᏴ, then there exists a sequence (bn)nNas in (i).

Thet-normTM is an trivial example of at-norm ofH-type, but there aret-normsT of Hadˇzi´c-type withT=TM(see, e.g., [3]).

Definition 1.2[3]. IfT is at-norm and (x1,x2,...,xn)[0, 1]n (nN), thenTin=1xi is defined recurrently by 1, ifn=0 andTin=1xi=T(Tin=11xi,xn) for alln1. If (xi)iNis a sequence of numbers from [0, 1], thenTi=1xiis defined as limn→∞Tin=1xi(this limit always exists) andTi=nxiasTi=1xn+i. In fixed point theory in probabilistic metric spaces there are of particular interest thet-normsT and sequences (xn)[0, 1] such that limn→∞xn=1 and limn→∞Ti=1xn+i=1. Some examples oft-norms with the above property are given in the following proposition.

Proposition1.3 [3]. (i)ForTTLthe following implication holds:

nlim→∞Ti=1xn+i=1⇐⇒

n=1

1xn

<. (1.3)

(ii)(1.3) also holds forT=TλSW.

(iii)IfT Ᏼ, then for every sequence (xn)nN in I such thatlimn→∞xn=1, one has limn→∞Ti=1xn+i=1.

(iv)IfT∈ {TλD,TλAA}, thenlimn→∞Ti=1xn+i=1

n=1(1xn)λ<.

Note [4, Remark 13] that ifTis at-norm for which there exists a sequence (xn)[0, 1]

such that limn→∞xn=1 and limn→∞Ti=1xn+i=1, then supt<1T(t,t)=1.

1.2. Menger spaces and generalized Menger spaces. Probabilistic contractions of Sehgal type. Let ∆+be the class of distance distribution functions[9], that is, the class of all functionsF: [0,)[0, 1] with the properties

(a)F(0)=0;

(b)Fis nondecreasing;

(c)Fis left continuous on (0,).

D+ is the subset of∆+ containing the functions F which also satisfy the condition limx→∞F(x)=1.

A special element ofD+is the functionε0, defined by ε0(t)=

0, ift=0,

1, ift >0. (1.4)

A sequence (Fn) in∆+is said to beweakly convergent toF+(shortlyFn−−→w F) if limn→∞Fn(x)=F(x) for every continuity pointxofF.

IfXis a nonempty set, a mappingF:X×X+is calleda probabilistic distance onX andF(x,y) is denoted byFxy.

The triple (X,F,T), where X is a nonempty set,F is a probabilistic distance onX, andT is at-norm, is calleda generalized Menger space(or aMenger space in the sense of

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Schweizer and Sklar) if the following conditions hold:

Fxy=ε0⇐⇒x=y, (1.5)

Fxy=Fyx, x,yX, (1.6)

Fxy(t+s)TFxz(t),Fzy(s), x,y,zX,t,s >0. (1.7) AMenger spaceis a generalized Menger space with the property Range (F)D+.

If (X,F,T) is a generalized Menger space with supt<1T(t,t)=1, then the family Uε,λ ε>0,λ(0,1), Uε,λ=

(x,y)X×X:Fxy(ε)>1λ (1.8) is a base for a metrizable uniformity onX, named theF-uniformityand denoted byᐁF.

Fnaturally determines a topology onX, calledtheF-topology:

OF⇐⇒ ∀xOε >0, λ(0, 1) such thatUε,λ(x)O. (1.9) ᐁFis also generated by the family{Vδ}δ>0whereVδ:=Uδ,δ. In what follows the topo- logical notions refer to theF-topology. Thus, a sequence (xn)nNisF-convergent toxX if for allε >0,λ(0, 1) there existskNsuch thatFxxn(ε)>1λfor allnk.

Definition 1.4. A sequence (xn)nN in X is calledF-Cauchyif for eachε >0,λ(0, 1) there existskNsuch thatFxrxs(ε)>1λfor allsrk.

Probabilistic contractions were first defined and studied byV. M. Sehgalin his doctoral dissertation at Wayne State University.

Definition 1.5[10]. LetSbe a nonempty set and letFbe a probabilistic distance onS.

A mapping f :SSis calleda probabilistic contraction(orB-contraction) if there exists k(0, 1) such that

Ff(p)f(q)(kt)Fpq(t), p,qS,t >0. (1.10) In [10] it is showed that any contraction map on a complete Menger space in which the triangle inequality is formulated under the strongest triangular normTM has a unique fixed point. In [11]Sherwoodshowed that one can construct a complete Menger space underTLand a fixed-point-free contraction map on that space.Hadˇzi´c[2] introduced the classᏴwhich have the property that Sehgal’s result can be extended to any continuous triangular norm in that class. Completing the result ofHadˇzi´c, Radusolved the problem of the existence of fixed points for probabilistic contractions in complete Menger spaces (S,F,T) withTcontinuous. Namely, the following theorem holds.

Theorem1.6 [7]. EveryB-contraction in a complete Menger space(S,F,T)withTcontin- uous has a (unique) fixed point if and only ifTis of Hadˇzi´c-type.

However, under some additional growth conditions on the probabilistic metricFone may replace the t-norm of H-type in the above theorem, as in Tardiff’s paper [13].

Corollary 2.6in our paper gives another result in this respect.

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2. Main results

The main result of this paper isTheorem 2.4concerning contractive mappings satisfying an implicit relation similar to that in [6,12]. This theorem generalizes the mentioned result of Hadˇzi´c (seeCorollary 2.7). Note that we work in generalized Menger spaces.

We begin with an auxiliary result, which is formulated as follows.

Lemma2.1. Let(X,F,T)be a generalized Menger space and let(xn)nNbe a sequence inX such that, for somek(0, 1),

Fxnxn+1(kt)Fxn1xn(t), n1,t >0. (2.1) If there existsγ >1such that

nlim→∞Ti=nFx0x1

γi=1, (2.2)

then(xn)nNis anF-Cauchy sequence.

Proof. First note [4] that if the condition limn→∞Ti=nFx0x1i)=1 holds for someγ= γ0>1, then it is satisfied for allγ >1. Indeed, if limn→∞Ti=nFx0x1i0)=1 andγγ0, then limn→∞Ti=nFx0x1i)limn→∞Ti=nFx0x10i)=1 and therefore limn→∞Ti=nFx0x1i)=1, while if γ < γ0, then γs> γ0, for some sN, and now limn→∞Ti=n+sFx0x1i) limn→∞Ti=nFx0x1i0)=1.

We will prove that

ε >0,n0=n0(ε) :Fxnxn+m(ε)>1ε, nn0,mN. (2.3) Letµ(k, 1) and letδ=k/µ. From the above remark it follows that

nlim→∞Ti=nFx0x1

1 µi

=1. (2.4)

Letε >0 be given andyi:=Fx0x1(1/µi). From limn→∞Ti=1yn+i=1 it follows that there existsn1Nsuch thatTim=1yn+i1>1ε, for allnn1, for allmN.

Since the seriesn=1δnis convergent, there existsn2Nsuch thatn=n2δn< ε.

Letn0=max{n1,n2}. Then, for allnn0andmN, we have Fxnxn+m(ε)Fxnxn+m

n+m1

i=n

δi

Tim=01Fxn+ixn+i+1

δn+iTim=01yn+i>1ε,

(2.5)

where the last “” inequality follows fromFxsxs+1s)=Fxsxs+1(k/µ)sFx0x1(1/µs) for all

s1, which immediately can be proved by induction.

In the following we deal with the classΦof all continuous functionsϕ: [0, 1]4R with the property:

ϕ(u,v,v,u)0=⇒uv. (2.6)

Next we give some examples of functions inΦ.

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Example 2.2. Ifa,b,c,dRanda+b+c+d=0, thenϕ(t1,t2,t3,t4) :=at1+bt2+ct3+ dt4Φif and only ifa+d >0.

Indeed,a+d0b+c0. Choosingu=0,v=1 we haveu < vandϕ(u,v,v,u)= (a+d)u+ (b+c)v=b+c0.

Conversely, if a+d >0 andϕ(u,v,v,u)0, then (a+d)u≥ −(b+c)v, that is (a+ d)u(a+d)v, which implies thatuv.

Thus, the functionsϕ1,ϕ2, ϕ1

t1,t2,t3,t4

=t1t2, ϕ2

t1,t2,t3,t4

=t1t3, (2.7)

are inΦ.

Also, the functionϕdefined byϕ(t1,t2,t3,t4)=t21t2t3and, more generally,ϕ(t1,t2, t3,t4)=t21(at22+bt32)t2t3witha+b=0 are inΦ.

In the proof of Theorem 2.4we need the following lemma, which is the analog of uniform continuity of a metric (note that ([0, 1],T) is rather a semigroup than a group).

Lemma2.3. Let(S,F,T)be a generalized Menger space withTcontinuous in(a, 1)for all a(0, 1), that is,

nlim→∞an=a, lim

n→∞bn=1=⇒lim

n→∞Tan,bn=a. (2.8) Ifp,qSand(pn)is a sequence inSsuch thatpnp, thenFpnq−−→w Fpq.

Proof. Letp,qS,pnpandtbe a continuity point ofFpq. By (1.7) it follows that for all 0< ε < t,

Fpnq(t)TFpnp(ε),Fpq(tε),

Fpq(t+ε)TFpnp(ε),Fpnq(t). (2.9) Therefore, limninfFpnq(t)Fpq(tε) andFpq(t+ε)limnsupFpnq(t). Lettingε0 we obtain limnsupFpnq(t)Fpq(t)limninfFpnq(t), and thus limn→∞Fpnq(t)=Fpq(t).

Theorem2.4. Let (X,F,T)be anF-complete generalized Menger space under a t-norm T which is continuous in(a, 1)for alla(0, 1),k(0, 1), andϕΦ. If f :XX is a mapping such that

ϕf

:ϕFf(x)f(y)(kt),Fxy(t),Fx f(x)(t),Fy f(y)(kt)0, x,yX,t >0 (2.10) and there existx0Xandγ >1for whichlimn→∞Ti=nFx0f(x0)i)=1, then f has a fixed point.

Proof. Letx0Xbe such that limn→∞Ti=nFx0f(x0)i)=1 and, for alln1,xn=f(xn1).

Note that (ϕf) implies that

Ff(x)f2(x)(kt)Fx f(x)(t), xX,t >0. (2.11)

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On taking in this relationx=xnwe obtain

ϕFxn+1xn+2(kt),Fxnxn+1(t),Fxnxn+1(t),Fxn+1xn+2(kt)0, nN,t >0. (2.12) It follows that Fxn+1xn+2(kt)Fxnxn+1(t), for all nN, for all t >0 and therefore, by Lemma 2.1, (xn) is a Cauchy sequence.

By theF-completeness ofXit follows that there existsuXsuch that limn→∞Fuxn(t)= 1, for allt >0.

Notice that from Fxn+1xn+2(kt)Fxnxn+1(t), for all nN, for all t >0 it follows that limn→∞Fxnxn+1(t)= 1, for all t > 0, for limn→∞Ti=nFx0f(x0)i) = 1 implies that limn→∞Fx0f(x0)n)=1 (thereforeFx0f(x0)D+) andFxnxn+1(t)Fx0x1(t/kn), for allnN, for allt >0.

Next, on takingx=xn,y=uin (ϕf) one obtains

ϕFxn+1f(u)(kt),Fxnu(t),Fxnxn+1(t),Fu f(u)(kt)0, nN,t >0. (2.13) Ifktis a continuity point ofFu f(u), then, on takingn→ ∞in the above inequality and usingLemma 2.3, we get

ϕFu f(u)(kt), 1, 1,Fu f(u)(kt)0. (2.14) ThusFu f(u)(kt)=1. SinceFu f(u)is increasing, the set of its discontinuity points is at most countable. HenceFu f(u)(kt)=1 for allt >0, from which (using (1.5)) we obtainu= f(u).

This completes the proof.

Corollary2.5 [5, Theorem 2.1]. Let(X,F,T)be anF-complete generalized Menger space under a continuoust-normTᏴ,k(0, 1), andϕΦ. If f :XXis a mapping such that

ϕFf(x)f(y)(kt),Fxy(t),Fx f(x)(t),Fy f(y)(kt)0, x,yX,t >0 (2.15) and there existsx0Xfor whichFx0f(x0)D+, thenf has a fixed point.

Proof. Choose a µ > 1. Since limn→∞µn = ∞ and Fx0x1 D+, it follows that limn→∞Fx0f(x0)n)=1. Therefore, byProposition 1.3(iii),

nlim→∞Ti=nFx0f(x0)

µi=1. (2.16)

Now applyTheorem 2.4.

Corollary2.6. Let(X,F,TL)be anF-complete generalized Menger space andϕΦ. If f :XXis a mapping such that

ϕFf(x)f(y)(kt),Fxy(t),Fx f(x)(t),Fy f(y)(kt)0, x,yX,t >0, (2.17) andn=1(1Fx0f(x0)n))<for somex0Xandγ >1, then f has a fixed point.

For the proof seeProposition 1.3.

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Corollary 2.7. Let (X,F,T) be an F-complete generalized Menger space under T {TλD,TλAA},k(0, 1), andϕΦ. If f :XXis a mapping such that

ϕFf(x)f(y)(kt),Fxy(t),Fx f(x)(t),Fy f(y)(kt)0, x,yX,t >0 (2.18) andn=1(1Fx0f(x0)n))λ<for somex0Xandγ >1, thenf has a fixed point.

Corollary2.8. Let(X,F,T)be anF-complete generalized Menger space under a continu- oust-normTandk(0, 1). If f :XXis a mapping satisfying one of the following conditions:

Ff(x)f(y)(kt)Fxy(t), x,yX,t >0, (2.19) F2f(x)f(y)(kt)Fxy(t)Fx f(x)(t), x,yX,t >0, (2.20) Ff(x)f(y)(kt)2Fxy(t)Fx f(x)(t), x,yX,t >0 (2.21) and there existsx0Xfor whichFx0f(x0)D+, thenf has a fixed point.

As a final result for this section, we consider an example to see the generality of Theorem 2.4.

Example 2.9. LetX be a set containing at least two elements and the mappingF from X×Xto∆+, defined by

Fxy(t)=

0, ift1 1

2, ift >1 forx,yX,x=y, Fxx=ε0, xX. (2.22) It is easy to show (see [14]) that (X,F,TM) is a complete Menger space.

We are going to prove that the mapping f :XX, f(x)=x satisfies the contrac- tivity condition (2.21) from the above corollary withb=2,c= −1, however it is not a B-contraction (here we took advantage of working in+rather than inD+).

First, we show that

Fxy(kt) + 12Fxy(t), x,yX,t >0. (2.23) Indeed, the above inequality holds with equality ifx=y, while ifx=ythen the right- hand member is at most 1.

Next, for everyt(1, 1/k],Fxy(kt)=0, whileFxy(t)=1/2, which means that f is not a Sehgal contraction.

References

[1] G. Constantin and I. Istr˘at¸escu,Elements of Probabilistic Analysis with Applications, Mathe- matics and Its Applications (East European Series), vol. 36, Editura Academiei, Bucharest;

Kluwer Academic Publishers, Dordrecht, 1989.

[2] O. Hadˇzi´c,A generalization of the contraction principle in probabilistic metric spaces, Univ. u Novom Sadu Zb. Rad. Prirod.-Mat. Fak.10(1980), 13–21 (1981).

[3] O. Hadˇzi´c and E. Pap,Fixed Point Theory in Probabilistic Metric Spaces, Mathematics and Its Applications, vol. 536, Kluwer Academic Publishers, Dordrecht, 2001.

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[4] ,New classes of probabilistic contractions and applications to random operators, Fixed Point Theory and Applications (Chinju/Masan, 2001), vol. 4, Nova Science Publishers, New York, 2003, pp. 97–119.

[5] D. Mihet¸,A generalization of a contraction principle in probabilistic metric spaces, The 9th Inter- national Conference on Applied Mathematics and Computer Science, Cluj-Napoca, 2004.

[6] V. Popa,Fixed points for non-surjective expansion mappings satisfying an implicit relation, Bul.

S¸tiint¸. Univ. Baia Mare Ser. B Fasc. Mat.-Inform.18(2002), no. 1, 105–108.

[7] V. Radu,Some fixed point theorems in probabilistic metric spaces, Stability Problems for Stochas- tic Models (Varna, 1985), Lecture Notes in Math., vol. 1233, Springer-Verlag, Berlin, 1987, pp. 125–133.

[8] , Lectures on Probabilistic Analysis, Surveys, Lecture Notes and Monographs. Series on Probability, Statistics and Applied Mathematics, vol. 2, Universitatea din Timis¸oara, Timis¸oara, 1994.

[9] B. Schweizer and A. Sklar,Probabilistic Metric Spaces, North-Holland Series in Probability and Applied Mathematics, North-Holland Publishing, New York, 1983.

[10] V. M. Sehgal and A. T. Bharucha-Reid,Fixed points of contraction mappings on probabilistic metric spaces, Math. Systems Theory6(1972), 97–102.

[11] H. Sherwood,Complete probabilistic metric spaces, Z. Wahrscheinlichkeitstheorie und Verw.

Gebiete20(1971/72), 117–128.

[12] B. Singh and S. Jain,A quantitative generalization of Banach contractions, in preparation.

[13] R. M. Tardiff,Contraction maps on probabilistic metric spaces, J. Math. Anal. Appl.165(1992), no. 2, 517–523.

[14] E. Thorp,Best possible triangle inequalities for statistical metric spaces, Proc. Amer. Math. Soc.

11(1960), 734–740.

Dorel Mihet¸: Faculty of Mathematics and Computer Science, West University of Timisoara, Bd. V.

Parvan 4, 300223 Timisoara, Romania E-mail address:[email protected]

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