1. Introduction
In 1975, Mandelbrot [
1] introduced the concept of fractal theory, which studies patterns in the highly complex and unpredictable structures that exist in nature. In 1981, Hutchinson [
2] conceptualized a mathematical way to generate self-similar fractals from iterated function system (IFS). The IFS is a finite collection of continuous mappings on a complete metric space. It is known that a contraction map is also continuous. Banach [
3] proved that every contraction map on a complete metric space has a unique fixed point. The Banach fixed point theorem is a very effective and popular tool to prove the existence and uniqueness of solutions of certain problems arising within and beyond mathematics. Using Banach fixed point theorem, we can get an attractor or a fractal by iteration of a finite collection of contraction maps of an IFS. An attractor is usually a non-empty self-similar set as it satisfies a self-referential equation, and it is a compact subset of a complete metric space. The IFS theory is used to construct fractal interpolation functions (FIFs) to model various complex scientific and natural phenomena. The fractal theory has found applications in diverse areas such as learning automata, modelling, image processing, signal processing, approximation theory, study of bio-electric recordings, etc. (see [
4,
5,
6,
7,
8,
9,
10,
11,
12]).
The framework of IFS theory has been extended to generalized contractions, countable IFSs, multifunction systems and more general spaces by many authors in the last two decades, see for instance [
13,
14,
15,
16,
17,
18,
19]. In particular, Mihail and Miculescu [
20,
21] considered mappings from a finite Cartesian product 
 into 
X instead of self-mappings of a metric space 
X. Dumitru [
22] enhanced the work of Miculescu and Mihail by taking a generalized IFS composed of Meir–Keeler type mappings. A similar extension performed by Strobin and Swaczyna [
23] with a generalized IFS consisting of 
-contractions. Secelean [
24] explored the IFSs composed of a countable family of Meir–Keeler contractive and 
-contraction maps. Again, he [
25] extended some fixed point results from the classical Hutchinson–Barnsley theory of IFS consisting of Banach contractions to IFS consisting of 
F-contractions. A multivalued approach of infinite iterated function systems accomplished by Leśniak [
26]. Jeli and Samet [
27] proposed a new type of contractive mappings known as 
-contraction (or JS-contraction), and they proved a fixed point result in generalized metric spaces. In addition, they demonstrated that the Banach fixed point theorem remains as a particular case of 
-contraction.
In the present paper, we propose an extension of IFS theory by including the left end-points of the domain and range of 
-functions. The new system is called generalized 
-contraction IFS, and it consists of a finite collection of 
-contraction functions on a complete metric product space. Every 
-contraction IFS is an IFS, but the converse is not generally true, hence the set of attractors for the 
-contraction IFSs is a broader family than the set of attractors of the IFSs. This paper is organized as follows: We discuss the basics and elementary properties of IFS, 
-contractions, multivalued map, and code space in 
Section 2. In 
Section 3, we construct generalized 
-contraction IFSs and prove the existence and uniqueness of its attractor. Further, we present the results for attractors of IFSs consisting of countable and multivalued 
-contraction maps in 
Section 4. Finally in 
Section 5, we demonstrate the relation between the codes space and the attractor of 
-contraction IFS, when the map 
 is continuous.
  2. Preliminary Facts
We discuss some basics and elementary results on iterated function systems, 
-contractions, multivalued map, and code spaces in this section. The details can be found in the references [
3,
25,
27,
28,
29].
Definition 1. A mapping  on a metric space  is called a contraction mapping if there is a constant  such that where k is called contractivity factor for T. In most of the text, this map is also called contractivity map.
 Banach [
3] proved that if 
 is a contraction map on a complete metric space 
, then 
T has unique fixed point 
. Moreover, 
 for each 
.
Let 
 be the set of all non-empty compact subsets of a metric space 
. It is a metric space with the Hausdorff metric 
h defined by
      
      where 
. The space 
 is called Hausdorff metric space. If 
 is complete (compact) metric space, t hen 
 is also complete (compact) metric space, respectively.
Lemma 1 ([
28]). 
If  are two arbitrary collections of sets in , then Lemma 2 ([
25]). 
If  is a sequence of contractive maps on a metric space  and point-wise convergent to a map T on X, then  (defined on compacts) is point-wise convergent to T with respect to the Hausdorff metric. Lemma 3. Let  for some metric space . Then for any , there exists  such that . Also, there are  in E and  in F such that .
 Proof.  Let . By compactness of F, there exists  such that . Thus .
Suppose 
 then by compactness of 
E, there exists 
 such that
        
        and by compactness of 
F, there exists 
 such that
        
Similarly, we can prove for the case     □
 Definition 2. An iterated function system (IFS)  on a topological space X is given by a finite set of continuous maps , where  is the set of the first N natural numbers. If X is a complete metric space and the maps  are contraction mappings with contraction factors , , then the IFS is said to be hyperbolic.
 Note that each map 
 on a topological space 
X induces a map 
 on its hyperspace 
 for 
, and we will use this notion throughout the paper. A hyperbolic IFS induces a map 
 defined by 
 In fact, 
 is also contracting with contractivity factor 
, and 
k is called the contractivity of the IFS. Barnsley [
28] proved every IFS on a complete metric space has a unique invariant set 
A(say) in 
 such that
      
Moreover,  for any . This set A is called the attractor. It is also called self-similar set or fractal. The above map  is called the Hutchinson operator for the corresponding IFS.
Jleli and Samet [
27] proposed a novel type of contractive maps, and proved a new fixed point theorem for such maps in the framework of generalized metric spaces. Consistent with [
27], we define a similar class of maps on a metric space by modifying the left end-points of domain and range:
Definition 3. We take Θ be the set of functions  satisfying the following conditions:
 θ is non-decreasing,
  for each sequence  if and only if 
  there exists  and  such that 
 Let , and , for some . Observe that 
Definition 4. A map T on a metric space  into itself is called -contraction, if T satisfies the following condition: where  and .
 Example 1. Let  defined by  and  defined by Clearly, . Our claim is, T is a -contraction with the usual metric. It is enough to prove  Remark 1. - (i)
 If T is a contraction map with contractivity factor r, then T is a -contraction map, where  and 
- (ii)
 Every -contraction map on a metric space  is continuous on X, and moreover, a -contraction map T is contractive in the sense that - (iii)
 It is easy to see the following implications: 
 Definition 5 ([
30]). 
An operator  is a Picard operator if T has a unique fixed point  and  as  for all . Theorem 1 ([
27]). 
Let  be a complete metric space and  be a given map. Suppose that there exist  and  such thatThen T is a Picard operator.
 Corollary 1. Let  be a -contraction on a complete metric space , then T is a Picard operator.
 Let X and Y be two metric spaces. A map  is called multivalued if for every ,  is a non-empty closed subset of Y. The point-to-set mapping  extends to a set-to-set mapping by taking  For a multivalued map , denote  and .
Definition 6. If  and  is a multivalued map, then a point  is called a fixed point of T provided . Thus, the set of fixed point of T is given by .
 Definition 7 ([
29]). 
A multivalued map  is called- (i)
 upper semicontinuous (u.s.c) if  is open in X for all open sets ,
- (ii)
 lower semicontinuous (l.s.c) if  is open in X for all open sets .
 Theorem 2 ([
29]). 
A mapping  is Hausdorff continuous if and only if it is both u.s.c. and l.s.c. Lemma 4 ([
29]). 
Let  be an u.s.c and . Then  Definition 8. Let  be a code space on N symbols , with the metric  defined by where , and 
   3. Generalized -Contraction Iterated Function Systems
Definition 9. A θ-contraction IFS is a finite collection of -contraction maps  on a complete metric space .
 Lemma 5. If f is a continuous map on a metric space  into a metric space , A is a compact subset of X and θ is a non-decreasing self map on , then 
 Proof.  Since 
 is non-decreasing,
        
By continuity of 
f and compactness of 
A, there exists 
 such that 
 Therefore,
        
Combining the above two inequalities, we get the desired result.    □
 We introduce the following concepts for our results in this section:
- (i)
 Let 
 be a metric space, we define a metric 
 on 
, (
m-times) for some 
 as follows
          
- (ii)
 For any map , define a corresponding self-map  on X is .
- (iii)
 Let  and , define the iterative sequence  of the map T at the point x as 
Definition 10. Let  be a map for some . Then we say that  is a fixed point of T if .
 Definition 11. A map  is called a generalized  contraction on a metric space , if T satisfies the following condition: where  and .
 Note that, if we take 
 in the above definition, we get the map 
T as a 
-contraction on 
. Every generalized 
-contraction is uniformly continuous because of that,
      
Theorem 3. Let  be a generalized -contraction on a complete metric space  for some . Then T satisfies the following properties:
- (i)
 T has a unique fixed point  and for any 
- (ii)
 The iterative sequence  of f at any point in  converges to .
 Proof.  Observe that,  is a -contraction on . Therefore,  for any , where  is the unique fixed point of .
Let 
 and 
. Then for all 
, there exists 
 such that 
. Thus, we obtain
        
From the above inequality, we conclude that     □
 Theorem 4. If a map  is a generalized -contraction on a metric space , then the set-valued map  is also a generalized -contraction on .
 Proof.  Let 
 and 
. Then, there exists 
 such that 
. Consider,
        
Since x is arbitrary, 
Therefore, using Lemma 5, we have
        
Similarly, we can prove 
By the property 
, we conclude that,
        
□
 Definition 12. A generalized θ-contraction IFS is a finite collection of generalized -contraction maps  on a complete metric space .
 Theorem 5. Let  be a finite collection of generalized -contraction on a metric space , then the Hutchinson map  defined by  is also a generalized -contraction on  with the same θ and .
 Proof.  Let 
. Our claim is
        
By using Lemma 1 and the property 
, we have
        
Using Theorem 4 in the above inequality, we obtain
        
By the non-decreasing property of log and 
,
        
Since the logarithm is a one to one function,
        
Finally, using (
2) in (
1), we get the desired claim of this proof.    □
 Corollary 2. Every generalized θ-contraction IFS has a unique attractor A (say), and the iterative sequence at any point  of the corresponding Hutchinson map  converges to A, that is  Proof.  Since,  is complete, then  is also complete. The proof follows from sequential use of Theorems 3–5.    □
 Note that the concept of -contraction is a particular case of generalized -contraction. The proofs of the following two theorems are straightforward by taking  in Theorems 4 and 5, respectively, and hence omitted.
Theorem 6. Let  be a -contraction on a metric space , then the set-valued map  is also a -contraction on  with the same θ and k.
 Theorem 7. Let  be a finite collection of -contractions on a metric space , then the Hutchinson map  defined by  is also a -contraction on  with the same  and .
 Corollary 3. Every θ-contraction IFS has a unique attractor A (say) and moreover, the
corresponding Hutchinson operator  is a Picard operator, that is  Proof.  By Theorem 7,  is a -contraction IFS on the complete metric space . From Corollary 1, we conclude that  is a Picard operator.    □
 Theorem 8. Let  be a sequence of θ-contraction IFSs. Assume that the following conditions are satisfied:
- (i)
 For all  is a -contraction map on a complete metric space  with θ-continuous and for each .
- (ii)
 The sequence  converges point-wise to a map 
- (iii)
 For all  is the attractor of the IFS  and the sequence  converges to a non-empty compact set A with respect to the Hausdorff metric.
- (iv)
 For all  is the Hutchinson operator of the IFS , i.e. .
Then  is also a θ-contraction IFS and  converges point-wise to the map , where  is the Hutchinson operator of the IFS . In addition, A is the attractor of the IFS .
 Proof.  (i) Let 
. By the given assumptions,
        
        Taking logarithms on both sides we get,
        
        Let 
. Taking limit as 
 on both sides and by continuity of 
, we conclude
        
        The above inequality proves that 
’s are 
-contractions, and by using Lemma 2, we obtain that 
 convergent point-wise to the map 
.
(ii) Since 
’s are 
-contractions, where 
 for each 
 thus 
’s are contractive maps. Therefore,
        
        Taking limit as 
 in the above inequality, we conclude 
.    □
   4. Countable and Multivalued -Contraction Iterated Function Systems
In this section, motivated by the work of Secelean [
24] and Leśniak [
26], we utilize our results to show the existence and uniqueness of attractors of countable and multivalued 
-contraction IFSs, respectively, by proving the corresponding the set valued map is a Picard operator.
Theorem 9. Let  be a sequence of -contraction functions on a compact metric space , where θ is left continuous and . Then the map  defined by  is a -contraction.
 Proof.  Let 
. By Lemma 1 and the property 
,
        
Since 
 is non-decreasing and left continuous,
        
Using (
4) in (
3), we conclude the proof.    □
 Corollary 4. If  is a sequence of -contraction functions on a compact metric space, where θ is left continuous and , then the map  defined as in the above statement is a Picard operator.
 Definition 13. A countable collection of -contraction maps  on a compact metric space, where θ is left continuous and  is called a countable θ-contraction IFS.
 Definition 14. A multivalued map  is said to be a multivalued -contraction on a metric space , if there exists  and  such that  Definition 15. A finite collection of multivalued -contraction maps on a complete metric space is called a multivalued θ-contraction IFS.
 If a map 
T is a multivalued 
-contraction on a metric space 
, then 
T is continuous on 
X, and it satisfies
      
Theorem 10. Let , be a finite collection of multivalued -contraction on a metric space , then the map  defined by  is a -contraction on the metric space , where .
 Proof.  By Theorem 2 and Lemma 4, 
 is well defined. Let 
 and choose 
 such that 
. Then there exists 
 and 
 such that 
 and there exists 
 such that 
. Then we have,
        
Combining the above two inequalities, we obtain
        
        and hence the proof.    □
 Corollary 5. If , is a finite collection of multivalued -contractions on a complete metric space, then the map  defined as in the above statement is a Picard operator.
   5. Code Space and Attractor of -Contraction IFS
Our goal is to construct a continuous transformation 
 from the code space onto the attractor of a restrictive class 
 of 
-contraction IFS so that it generalizes the classical result proved in Barnsley [
28] for usual contractions.
Definition 16. Let Ω be the set of functions  satisfying the following conditions:
 θ is nondecreasing,
  for each sequence  if and only if ,
  there exists  and  such that 
 θ is continuous.
 Note that  is a subset of the collection .
Lemma 6. Let  be a family of -contraction maps on a complete metric space , where . Let . Then there exists  such that , and the restriction maps  on  forms a θ-contraction IFS. In other words, 
 Proof.  Take  for all  as a condensation set. Denote as  and  the Hutchinson operators for the -contraction IFSs  and , respectively. By Theorem 7, both  and  are -contractions with 
By Corollary 3, 
 converges to an attractor 
 (say). Observe that 
 is an increasing sequence, i.e.,
        
        and
        
Therefore, we have
        
        where 
 means the closure of 
A. Observe that 
 and 
. Therefore, the set 
 satisfies the desired conclusion.    □
 Lemma 7. Let  be a family of -contraction maps on a complete metric space , where . Denote Let . Then there exists a finite constant λ such that where 
 Proof.  Let 
 and 
. By Lemma 6, there exists 
 such that 
. Consider
        
        where 
 and 
 Therefore, we have
        
        where 
 By continuity of 
 and compactness of 
, 
 is finite.    □
 Theorem 11. Let  be a family of -contraction maps on a complete metric space , where . Let A denote the attractor of a θ-contraction IFS . Define a map  by is well-defined ( the limit exists, belongs to A and is independent of ), continuous and onto, where φ is defined as in Lemma 7.
 Proof.  Our first claim is that 
 is well defined. It’s enough to prove the existence and independence of 
x of
        
Let 
 such that 
 and 
. According to Lemma 7,
        
Therefore, 
 exists. It is easy to observe that 
, where 
 is the Hutchinson operator. From Corollary 3,  
 is a Picard operator, and consequently, 
. Suppose 
 and 
 for some 
 and 
. Let 
. Then there exists 
 such that for all 
,
        
Consider
        
        and
        
        which is a contradiction to (
5). Therefore, the limit of the sequence 
 is independent of 
x.
Our next claim is 
 is continuous. Let 
. Then, there exists 
 such that
        
        where 
 is defined from 
M as in Lemma 6. The above inequality is true because 
 is not depending on 
 in 
Let 
. Since 
, we have
        
This implies
        
        where 
Taking limits as 
, we have
        
Finally, we need to prove 
 is onto. Let 
. Since 
 there exists a sequence 
 such that
        
By the compactness of 
, there exists a convergent subsequence 
, whose limit is 
. For all 
, define 
 as the number of elements in 
, 
 Consider
        
        for some 
 Observe that 
 as 
 Therefore,
        
Hence the proof.    □
 Definition 17. Suppose A is the attractor of a θ-contraction IFS , where  is -contraction on a complete metric space  and . Let  defined as in Theorem 11. For any , is called the set of addresses of .
 When we assume the map  is continuous, then it is possible to compute the addresses for each point on the attractor of -contraction IFS as per the description given in Definition 17.