1 Introduction

Probabilistic metric space has been introduced and studied in 1942 by Menger in USA [1], and since then the theory of probabilistic metric spaces has developed in many directions [26]. The idea of Menger was to use distribution functions instead of nonnegative real numbers as values of the metric. The notion of a probabilistic metric space corresponds to the situation when we do not know exactly the distance between two points, we know only probabilities of possible values of this distance. Such a probabilistic generalization of metric spaces appears to be well adapted for the investigation of physiological thresholds and physical quantities, particularly in connection with both string and E-infinity which were introduced and studied by a well-known scientific hero El Naschie [79].

It is observed by many authors that the contraction condition in a metric space may be exactly translated into a probabilistic metric space endowed with min norms. Sehgal and Bharucha-Reid [10] obtained a generalization of the Banach contraction principle on a complete Menger space, which is a milestone in developing fixed point theorems in a Menger space.

Jungck’s fixed point theorem [11] has many applications in nonlinear analysis. This theorem is extended by several authors; see [1216] and the references therein.

In this paper, we introduce a new class of Jungck-type contraction and present some common fixed point theorems for this mapping. Several examples are given to show that our result is a proper extension of many known results.

2 Preliminaries

Throughout this paper we denote by N the set of all positive integers, by Q the set of all rational numbers, by Z + the set of all nonnegative integers, by R the set of all real numbers and by R + the set of all nonnegative real numbers. We shall recall some definitions and lemmas related to a Menger space.

Definition 2.1 A mapping F:R R + is called a distribution if it is nondecreasing left continuous with inf{F(t):tR}=0 and sup{F(t):tR}=1. We shall denote by L the set of all distribution functions. The specific distribution function H:R R + is defined by

H(t)={ 0 , t 0 , 1 , t > 0 .

Definition 2.2 ([13])

Probabilistic metric space (PM-space) is an ordered pair (X,F), where X is an abstract set of elements and F:X×XL is defined by (p,q) F p , q , where { F p , q :p,qX}L, where the functions F p , q satisfy the following:

  1. (a)

    F p , q (x)=1 for all x>0 if and only if p=q;

  2. (b)

    F p , q (0)=0;

  3. (c)

    F p , q = F q , p ;

  4. (d)

    F p , q (x)=1 and F q , r (y)=1, then F p , r (x+y)=1.

Definition 2.3 A mapping t:[0,1]×[0,1][0,1] is called a t-norm if

  1. (e)

    t(0,0)=0 and t(a,1)=a for all a[0,1];

  2. (f)

    t(a,b)=t(b,a) for all a,b[0,1];

  3. (g)

    t(a,b)t(c,d) for all a,b,c,d[0,1] with ac and bd;

  4. (h)

    t(t(a,b),c)=t(a,t(b,c)) for all a,b,c[0,1].

Definition 2.4 A Menger space is a triplet (X,F,t), where (X,F) is a PM-space and t is a t-norm such that for all p,q,rX and all x,y0,

F p , r (x+y)t ( F p , q ( x ) , F q , r ( y ) ) .

Definition 2.5 ([13])

Let (X,F,t) be a Menger space and f:XX.

  1. (1)

    A sequence { p n } in X is said to converge to a point p in X (written as p n p) if for every ε>0 and λ>0, there exists a positive integer M(ε,λ) such that F p n , p (ε)>1λ for all nM(ε,λ).

  2. (2)

    A sequence { p n } in X is said to be Cauchy if for each ε>0 and λ>0, there is a positive integer M(ε,λ) such that F p n , p m (ε)1λ for all n,mN with n,mM(ε,λ).

  3. (3)

    A Menger space (X,F,t) is said to be complete if every Cauchy sequence in X converges to a point of it.

  4. (4)

    f is said to be continuous at a point p in X if for every sequence { p n } in X, which converges to p, the sequence {f( p n )} in X converges to f(p).

  5. (5)

    f is said to be continuous on X if f is continuous at every point in X.

Definition 2.6 ([4])

A t-norm t is said to be of H-type if a family of functions { t n ( a ) } n = 1 is equicontinuous at a=1, that is, for any ε(0,1), there exists δ(0,1) such that a>1δ and n1 imply t n (a)>1ε. The t-norm t=min is a trivial example of a t-norm of H-type, but there are t-norms of H-type with t-normmin (see, e.g., Hadzic [5]).

From Definition 2.1-Definition 2.5, we can prove easily the following lemmas.

Lemma 2.7 ([10])

If (X,d) is a metric, then the metric induces a mapping X×XL, defined by F p , q (x)=H(xd(p,q)), p,qX and xR. Further, if the t-norm t:[0,1]×[0,1][0,1] is defined by t(a,b)=min{a,b} for all a,b[0,1], then (X,F,t) is a Menger space. It is complete if (X,d) is complete.

Lemma 2.8 In a Menger space (X,F,t), if t(x,x)x for all x[0,1], then t(a,b)=min{a,b} for all a,b[0,1].

3 Jungck-type fixed point theorems

In 1976, Jungck proved the following theorem.

Theorem A (Jungck [11], 1976)

Let f be a continuous mapping of a complete metric space (X,d) into itself and let g:XX be a map that satisfies the following conditions:

for all x,yX and for some 0<k<1. Then f and g have a unique common fixed point.

Definition 3.1 Let (X,F,t) be a Menger space with t(x,x)x for all x[0,1] and let f,g:XX be two self-mappings of X. We will say that f and g are Jungck-type generalized contraction if

for all p,qX and x>0, where φ:[0,)[0,) is a mapping such that φ(x)<x for all x>0, and for all p,qX and xR, F p , q (x) is the same as in Definition 2.2.

Remark 3.2

  1. (1)

    It is clear that (∗1) implies (∗2) if F p , q (x)=H(xd(p,q)) for all p,qX, xR, and φ(x)=kx for all x R + , where 0<k<1.

  2. (2)

    In Example 3.10, we shall show that the condition (∗2) is satisfied, but the condition (∗1) is not satisfied.

Definition 3.3 Let φ:[0,)[0,) be a mapping such that φ(x)<x for all x>0. We say that φ is the U-generalized contraction if

for all x>0 and r Z + .

Lemma 3.4 Let k(0,1) be as in (c) of Theorem  A and let φ:[0,)[0,) be defined by

φ(x)={ ( 1 + k 2 ) x + ( 1 k 2 ) x 2 , 0 x k , ( 1 2 + k k 2 2 ) x , k < x .

Then φ is an U-generalized contraction.

Proof It follows from hypotheses that for all x>0,

Now we shall show that condition (∗3) is satisfied. Since

( x φ ( x ) ) ( φ ( x ) x ) r kfor all x(0,k] and r Z + ,

there are three cases which need to be considered.

Case 1. Let x(0,k] and r Z + . Then, since

( 1 φ ( x ) x ) ( φ ( x ) x ) r 1,

(∗3) is satisfied.

Case 2. Let x(k,) and r Z + with (xφ(x)) ( φ ( x ) x ) r k. Then, since

( 1 + k 2 ) + ( 1 k 2 ) ( x φ ( x ) ) ( φ ( x ) x ) r 1 2 +k k 2 2 ,

(∗3) is satisfied.

Case 3. Let x(k,) and r Z + with k<(xφ(x)) ( φ ( x ) x ) r . Then, since

1 2 +k k 2 2 = φ ( x ) x ,

(∗3) is satisfied. From (∗4), Case 1, Case 2 and Case 3, φ is U-generalized contraction. □

The following example shows that f and g do not have a common fixed point even though f, g and φ satisfy (∗2) and (∗3).

Example 3.5 Let k(0,1) and φ:[0,)[0,) be as in Lemma 3.4. Let f,g:RR be defined by f(x)=x+1 and g(x)= k 2 x. Define F p , q :R R + by

F p , q (x)=H ( x | p q | ) for all p,qR and xR,

where F p , g and H are the same as in Definition 2.1 and Definition 2.2. Let t:[0,1]×[0,1][0,1] be defined by t(a,b)=min{a,b} for all a,b[0,1]. Then, by Lemma 3.4 and simple calculations, (∗2) and (∗3) are satisfied. But f and g do not have a common fixed point.

Remark 3.6 It follows from Example 3.5 that f and g must satisfy (∗2) and (∗3), and other conditions additionally in order to have a common fixed point of f and g.

The following is Jungck-type common fixed point theorem which is a generalization of Jungck’s common fixed point theorem [11].

Theorem 3.7 Let (X,F,t) be a complete Menger space with continuous t-norm and t(x,x)x for all x[0,1], let f be a continuous self-mapping on X and let φ: R + R + be a mapping that satisfies the following conditions:

  1. (i)

    g(X)f(X);

  2. (ii)

    g commutes with f;

  3. (iii)

    f, g and φ satisfy (∗2) and (∗3);

  4. (iv)

    φ is a strictly increasing and bijective;

  5. (v)

    lim n φ n (x)= for each x>0, where φ n is n-times repeated composition of φ 1 with itself.

Then f and g have a unique common fixed point.

Proof

It is easy to see that the self-mapping  g  on  X  in Theorem 3.7 is continuous on  X .
(3.1)

Let x 0 X. By (i), there exists a sequence { x n } n = 0 in X such that

f( x n )=g( x n 1 )for all nN.
(3.2)

From (iii) and (3.2), we have

F g ( x n 1 ) , g ( x n ) ( φ ( x ) ) F f ( x n 1 ) , f ( x n ) (x)for all nN and x>0.
(3.3)

By virtue of (iv), (3.2) and (3.3), we obtain

F f ( x n ) , f ( x n + 1 ) (x)= F g ( x n 1 ) , g ( x n ) (x) F f ( x n 1 ) , f ( x n ) ( φ 1 ( x ) )
(3.4)

for all nN and x>0. In view of (3.4), we have

F f ( x n ) , f ( x n 1 ) (x) F f ( x 0 ) , f ( x 1 ) ( φ n ( x ) )
(3.5)

for all nN and x>0. By repeated application of (3.5), we have

F f ( x n + j ) , f ( x n + 1 + j ) (x) F f ( x n ) , f ( x n + 1 ) ( φ j ( x ) )
(3.6)

for all n,jN and x>0. From (iii), we have

0< φ ( x ) x <1for all x>0.
(3.7)

On account of (3.7), we obtain that

k = 0 [ φ ( x ) x ] k = 1 1 ( φ ( x ) x ) for all x>0.
(3.8)

In terms of (3.8), we get that

x= ( x φ ( x ) ) k = o ( φ ( x ) x ) k for all x>0.
(3.9)

Now we shall show that {f( x n )} is a Cauchy sequence.

Let n,mN be such that n<m.
(3.10)

From (iii), (iv), (3.5)-(3.10) and Definition 2.4, we deduce that

F f ( x n ) , f ( x m ) ( x ) = F f ( x n ) , f ( x m ) ( ( x φ ( x ) ) k = 0 ( φ ( x ) x ) k ) F f ( x n ) , f ( x m ) ( ( x φ ( x ) ) k = 0 m n 1 ( φ ( x ) x ) k ) min { F f ( x n ) , f ( x n + 1 ) ( ( x φ ( x ) ) ) , F f ( x n + 1 ) , f ( x n + 2 ) ( ( x φ ( x ) ) ( φ ( x ) x ) ) , , F f ( x m 1 ) , f ( x m ) ( ( x φ ( x ) ) ( φ ( x ) x ) m n 1 ) } min { F f ( x n ) , f ( x n + 1 ) ( ( x φ ( x ) ) ) , F f ( x n ) , f ( x n + 1 ) ( φ 1 ( ( x φ ( x ) ) ( φ ( x ) x ) ) ) , , F f ( x n ) , f ( x n + 1 ) ( φ ( m n 1 ) ( ( x φ ( x ) ) ( φ ( x ) x ) m n 1 ) ) } F f ( x n ) , f ( x n + 1 ) ( ( x φ ( x ) ) ) F f ( x 0 ) , f ( x 1 ) ( φ n ( x φ ( x ) ) )
(3.11)

for all x>0 and n,mN with n<m. In terms of (iii), (v) and Definition 2.2, we have

lim n F f ( x 0 ) , f ( x 1 ) ( φ n ( x φ ( x ) ) ) =1for all x>0.
(3.12)

By (3.11), (3.12) and Definition 2.2, {f( x n )} is a Cauchy sequence in X. Since X is complete and {f( x n )} is a Cauchy sequence in X, there exists zX such that

lim n f( x n )=z.
(3.13)

On account of (3.2) and (3.13), we have

lim n g( x n )=z.
(3.14)

By (ii), (3.1), (3.13), (3.14) and hypotheses,

f ( g ( x n ) ) = g ( f ( x n ) ) for all  n N , lim n f ( g ( x n ) ) = f ( z )
(3.15)

and

lim n g ( f ( x n ) ) =g(z).

From (3.15), we get that

f(z)=g(z).
(3.16)

In view of (ii), (3.16) and (∗2), we have

F g ( z ) , g ( g ( z ) ) ( φ ( x ) ) F f ( z ) , f ( g ( z ) ) ( x ) F g ( z ) , g ( f ( z ) ) ( x ) F g ( z ) , g ( g ( z ) ) ( x )
(3.17)

for all x>0.

By (iv) and (3.17),

F g ( z ) , g ( g ( z ) ) (x) F g ( z ) , g ( g ( z ) ) ( φ n ( x ) )
(3.18)

for all nN and x>0. Due to (v), (3.18), Definition 2.1 and Definition 2.2, we get that

g(z)=g ( g ( z ) ) .
(3.19)

From (ii), (3.16) and (3.19), we have

g(z)=g ( g ( z ) ) =g ( f ( z ) ) =f ( g ( z ) ) .
(3.20)

By (3.20), g(z) is a common fixed point of f and g. To prove the uniqueness of a common fixed point of f and g, let u and w be common fixed points of f and g. Then f(u)=g(u)=u and f(w)=g(w)=w. Putting p=u and q=w in (∗2), we get

F g ( u ) , g ( w ) ( φ ( x ) ) = F u , w ( φ ( x ) ) F f ( u ) , f ( w ) (x)= F u , w (x)
(3.21)

for all x>0, which gives u=w. Thus g(z) is a unique common fixed point of f and g. □

Now we give an example to support Theorem 3.7.

Example 3.8 Let X=R be the set of reals with the usual metric and let f,g:XX and φ: R + R + be mappings defined as follows:

f(x)=3x,g(x)=2xandφ(x)={ 2 3 x + 1 3 x 2 , 0 x 2 3 , 8 9 x , 2 3 < x .
(3.22)

Let the mappings F p , q , H and t be as in Example 3.5. Then from Lemma 2.7, (X,F,t) is a complete Menger space. By the same method as in Lemma 3.4 and simple calculations, the conditions of Theorem 3.7 are satisfied. Thus f and g have a unique common fixed point 0.

From Theorem 3.7, we have the following corollary.

Corollary 3.9 Let (X,F,t) be a complete Menger space with continuous t-norm and t(x,x)x for all x[0,1]. Let f,g:`XX be maps that satisfy the following conditions:

  1. (a)

    g(X)f(X);

  2. (b)

    f is continuous;

  3. (c)

    g commutes with f;

  4. (d)

    F g ( p ) , g ( q ) (kx) F f ( p ) , f ( q ) (x) for all p,qX, x>0 and for some 0<k<1. Then f and g have a unique common fixed point.

Proof Let φ: R + R + be defined by

φ(x)=kx,0<k<1.
(3.23)

From (b) and (d), we deduce that g is continuous. Thus, by (3.23), the same method as in Lemma 3.4 and simple calculations, the conditions of Theorem 3.7 are satisfied. Therefore f and g have a unique common fixed point.

In the next example, we shall show that all the conditions of Theorem 3.7 are satisfied, but condition (d) in Corollary 3.9 and condition (∗1) in Theorem A are not satisfied. □

Example 3.10 Let k(0,1) be as in (c) of Theorem A and let X=R be the set of reals with usual metric. Suppose that f,g:XX and φ: R + R + are mappings defined as follows:

f(x)=kx,g(x)= ( k + k 2 2 ) x

and

φ(x)={ ( 1 + k 2 ) x + ( 1 k 2 ) x 2 , 0 x k , ( 1 2 + k k 2 2 ) x , k < x .

Let the mappings F p , q , H and t be the same as in Example 3.5. Then, from Lemma 2.7 and Lemma 3.4, (X,F,t) is a complete Menger space and φ satisfies (∗3). Since

| g ( p ) g ( g ) | φ ( | f ( p ) f ( g ) | )

for all p,qX, we deduce that

F g ( p ) , g ( q ) ( φ ( x ) ) F f ( p ) , f ( q ) (x)

for all p,qX and x>0, which implies (∗2). By simple calculations, conditions (i), (ii), (iv) and (v) of Theorem 3.7 are satisfied. Thus all the conditions of Theorem 3.7 are satisfied. Hence f and g have a unique common fixed point 0. By hypotheses, there exist p 1 =kR, q 1 =0R and x 1 = 3 4 k 2 + 1 4 k>0 such that

F g ( p 1 ) , g ( q 1 ) (k x 1 )< F f ( p 1 ) , f ( q 1 ) ( x 1 ),

which implies that condition (d) of Corollary 3.9 is not satisfied. By hypotheses, there exist p 2 = k 2 R and q 2 =0R such that

| g ( p 2 ) g ( q 2 ) | >k | f ( p 2 ) f ( q 2 ) | ,

which implies that condition (∗1) in Theorem A is not satisfied. Therefore Theorem 3.7 is a proper extension of Theorem A and Corollary 3.9.

A natural question arises from Example 3.5.

Question Would Theorem 3.7 remain true if (i)-(v) in Theorem 3.7 were substituted by some suitable conditions?