Abstract
The aim of this paper is to propose a new faster iterative scheme (called -iteration) to approximate the fixed point of -enriched contraction mapping in the framework of Banach spaces. It is also proved that our iteration is stable and converges faster than many iterations existing in the literature. For validity of our proposed scheme, we presented some numerical examples. Further, we proved some strong and weak convergence results for b-enriched nonexpansive mapping in the uniformly convex Banach space. Finally, we approximate the solution of delay fractional differential equations using -iterative scheme.
Keywords:
AA-iterative scheme; fixed point; delay fractional differential equations; enriched contraction; enriched nonexpansive mapping MSC:
47H09; 47H10
1. Introduction and Preliminaries
The proof of the Banach contraction principle (BCP) [] is based on convergence of the most simplest iterative process named as the sequence of successive approximations or Picard iterative process. This principle solves a fixed point problem for contraction mapping defined on a complete metric space and has become an important tool to prove the existence and approximation of solutions of nonlinear functional equations such as differential equations, integral equations and partial differential equations. In certain cases, the existence of solution of fixed point problem is guaranteed, but finding the exact solution is not possible. In such a situation, an approximation of the solution of the given problem is much desired, which gave rise to development of the different iterative processes [,,,,,].
Many authors have proposed and applied different fixed point iterative schemes for approximation of the solution of linear and nonlinear equations and inclusion. It is always preferred to develop an iterative scheme, which is better than others in the sense that the solution is approximated in a fewer number of steps. In this paper, we shall develop an iterative process and compare it with some well-known iterative processes existing in the literature. Throughout this paper, the set is denoted by . Let U be a normed space, a nonempty closed convex, a nonempty bounded closed convex subsets of U and T a self mapping on . The set of all fixed points of T is denoted by
In 1991, Sahu [] proved the following:
Lemma 1
([]). Suppose that U is a uniformly convex Banach space and for all . Let and be two sequences in U such that
hold for some Then .
Recall that a mapping T is called Lipschitzian if there exists a constant such that
holds for all If we take in the above inequality, then T is called a contraction. The mapping T is called nonexpansive if we set in the above inequality.
Berinde [] introduced the concept of enriched nonexpansive mapping on a normed space as follows:
A self mapping T on is said to be an enriched nonexpansive if for all , there exists such that
To highlight the parameter b in T is termed as b-enriched nonexpansive mapping.
A mapping is said to be an enriched contraction [] if for all there exists and such that
Again to highlight the parameter b in T is called a -enriched contraction. It was shown that -enriched contraction mapping on has a unique fixed point, which can be approximated by means of the Krasnoselskii’s iterative scheme [].
Definition 1
([]). A mapping is said to be demiclosed at , if whenever a sequence in Ω and in U, it follows that
Lemma 2
([]). Let Ω be nonempty closed convex subset of a uniformly convex Banach space U and T a nonexpansive mapping on Ω. Then is demiclosed at zero.
Remark 1
([]). Let T be a self mapping on Ω. For any , the averaged mapping on Ω given by
has the property that . Clearly, and are the trivial cases.
There are several iterative processes which are used to approximate fixed point of a certain nonlinear operator. One of the most important factors to decide the preference of one iterative process over the other is the rate of convergence. In order to compare convergence rates between two iteration processes, we use the following useful definition of Berinde [].
Definition 2.
Suppose that sequences and converge to the same point with the following error estimates
If , then converges faster than .
Let us recall that for the given in the sequence defined by
is known as the sequence of successive approximations or Picard iteration []. The well-known Banach contraction principle states that converges to a unique fixed point of T for any choice of a starting point in provided that T is a contraction mapping. However, the Picard iteration does not need to converge to fixed point of nonexpansive mapping. For instance, the self mapping on does not converge to its fixed point for any choice of other than On the other hand, averaged operator for any converges to fixed point of T for any choice of x and hence in certain cases, it is useful to consider an averaged operator in an iterative scheme than a mapping T itself.
Let us choose an initial guess in The sequence defined by
is called Mann iteration sequence [], where the sequence of parameters in satisfies certain conditions.
The sequence defined by
is known as Ishikawa iteration scheme [], where and are some appropriate sequences in .
Noor [] proposed a three step iteration scheme to construct a sequence as follows:
where , in satisfy certain conditions.
In 2007, Agarwal et al. [] defined a sequence known as S-iteration scheme given by
where , are appropriate sequences in .
It was proved that the rate of convergence of iteration scheme (7) is same as the Picard iteration scheme but faster than Mann iteration scheme for the class of contraction mappings [].
An iterative scheme introduced in [] has a faster rate of convergence than iteration for approximating the fixed points of contraction mappings. This scheme is given as:
where and in satisfy certain appropriate conditions.
An iterative sequence
proposed by Thakur et al. [] has a better rate of convergence than iterative sequence in [], where the sequences and are given sequences in .
In 2018, Ullah et al. [] introduced M-iteration sequence as follows
for approximating the fixed points of Suzuki’s generalized nonexpansive mappings, where .
Ali et al. [] modified an M-iteration sequence by introducing F-iteration sequence given by
where . They showed that F-iteration sequence has a better rate of convergence than M-iteration and all other iterative schemes presented in [].
For practical purposes, we deal with an approximate sequence we obtain it because of numerical approximation of operator and round off errors, instead of a theoretical sequence obtained through an iterative process for some given function f.
The approximate sequence converges to fixed point of T if and only if the given fixed point iterative scheme is stable. The notion of the stability for a fixed point iterative scheme was introduced by Ostrowski [].
Definition 3.
Let be an approximate sequence of in a subset Ω of a Banach space U. Then a given iterative process for some function f, converging to a fixed point of self mapping T on Ω, is said to be T-stable or stable with respect to T provided that if and only if , where is given by
Following results are needed in the sequel.
Lemma 3
([]). Let and be sequences of positive real numbers satisfying the following inequality:
where for all with . If then .
Question: Continuing in this direction, we pose the following question:
To answer the above question in affirmative, we introduce an -iterative scheme for an averaged mapping to approximate the fixed points of enriched contraction mappings as follows:
where and are sequences of parameters in .
The aim of this paper is to show that an -iterative scheme has a faster rate of convergence than –. Strong and week convergence results are also established for a b-enriched nonexpansive mapping. Numerical examples are presented to compare the rate of convergence with Ishikawa, Noor, Agarwal et al., Abbas et al. and Thakur et al., M-iteration and F-iteration for classes of contraction and -enriched contraction mappings. As an application, we approximate the solution of delay fractional differential equations by using our proposed scheme.
2. Convergence and Stability Results
In this section, we establish convergence and stability of AA-iterative scheme constructed with -enriched contractions mapping in arbitrary Banach space.
Theorem 1.
Let Ω be a nonempty closed and convex subset of a Banach space U and a -enriched contraction mapping with . Then, the sequence defined by converges to a fixed point of
Proof.
Take , it follows that . Then becomes
which can be written in an equivalent form as follows:
where . As , . Thus an averaged operator is a contraction with contractive constant . Let Then, we have
Further,
Moreover,
Note that
and
Now by , we have
Thus,
Inductively, we can obtain that
As , converges to . □
Theorem 2.
Let Ω be a closed convex subset of a uniformly convex Banach space U and T a -enriched contraction with . Suppose that the sequences , , , , , , , , given by iterative schemes , , , , , , , , , respectively, converge to . Then, converges at a rate faster than the other schemes.
Proof.
Let As proved in Theorem 3 of [], we have
Now, by in above theorem, we have
Then,
So, we have as . Definition (2) implies that converges faster than to the fixed point Now, the inequality proved in Theorem 3.1 of Thakur et al. []
Let
So,
So, we have as . It implies that converges faster than to the fixed point
Similarly, we can show that the sequence has better rate of convergence than all other sequences define above. □
Theorem 3.
Let Ω be a nonempty closed and convex subset of a Banach space U and a -enriched contraction mapping. Then, the iterative scheme defined in is -stable for .
Proof.
Let be an approximate sequence of in . The sequence defined by iteration is:
and ,
We need to show that if and only if
If , it follows from that
By Theorem 1, we have
Let
Then,
Since, , as
Now, by Lemma 3, we have and hence
Conversely, if then we have
This implies that Hence, the iterative scheme is -stable. □
We now present an example to support our assertion that our iterative process converges faster than all other iterative schemes considered herein for the class of -enriched contraction mappings.
Example 1.
Let and Let be a mapping given by for all Choose and , with the initial value of
Note that T is -enriched contraction with fixed point 5. So .
Our iteration , F-iteration M-iteration Thakur et al. Abbas and Nazir Agarwal et al. and Noor iterative processes are given in Table 1.
Table 1.
Convergence comparison of iterative schemes for -enriched contraction mapping.
Note that all sequences converge to . The comparison shows that our iteration scheme converges faster than all the other schemes.
Here we present another numerical example to support our claim.
Example 2.
Let , and Let be defined as
for all Choose and , with the initial value of
Our iteration scheme along with other iterative schemes for are given in Table 2.
Table 2.
Convergence comparison of iterative schemes for contraction mapping.
All sequences converge to The comparison shows that our iteration scheme has a better rate of convergence than other schemes.
In Table 1 we have the following observations regarding the convergence of fixed point of -enriched contraction mapping mapping by taking initial point . Observe that our iterative scheme converges to the fixed point in eight iterations while other described iterative schemes took more than 10 iterations for convergence.
In Table 2 we have the following observations regarding the convergence of fixed point of contraction mapping mapping by taking initial point . Observe that our iterative scheme converges to the fixed point in 12 iterations, Iteration in 14 iterations, M-iteration in 17 iterations and other iterative schemes took more than 30 iterations for convergence.
In Figure 1 and Figure 2, we test the convergence of different iteration processes for -enriched contraction and contraction, respectively. Observe that in both cases our iterative scheme is more stable and converges faster to their fixed points than other iterative scheme.
Figure 1.
Convergence behavior of our scheme, F-Iteration, M-Iteration, Thakur, Abbas, Agarwal and Noor iterations for -enriched contraction mapping given in Example 1.
Figure 2.
Convergence behavior of our scheme, F-Iteration, M-Iteration, Thakur, Abbas, Agarwal, Noor and Ishikawa iterations for contraction mapping given in Example 2.
3. Convergence Results for b-Enriched Nonexpansive Mappings
This section deals with some convergence results of an iterative process
Theorem 4.
Let be a nonempty closed bounded convex subset of a uniformly convex Banach space U and a b-enriched nonexpansive mapping. Then .
Proof.
Since T is a b-enriched nonexpansive mapping, take .It follows that . Then by we have
which can be written in equivalent form as
That is the averaged operator is nonexpansive. By means of the Browder’s fixed point theorem, it follows that has at least one fixed point. By remark 1 . □
Lemma 4.
Let be a nonempty bounded closed convex subset of a uniformly convex Banach space U and a b-enriched nonexpansive mapping. If is a sequence defined in and then exists for all
Proof.
By Theorem 4, an averaged operator is nonexpansive. Let Then,
Thus,
and
Now,
So, is a bounded monotone decreasing sequence. Therefore, exists for all □
Lemma 5.
Let T, and U be as given in Lemma 4 and a sequence defined by and Then , where
Proof.
Let Then, by Lemma 4, exists. Suppose that
By taking limit supremum as on both sides of –, we have
Since, is nonexpansive mapping, we have
By taking limit supremum on both sides, we obtain
Since,
So, from and , we have
and
So,
Taking lim inf as on both sides of the above, we obtain
This implies that
from , and and by Lemma 1, we have
□
Theorem 5.
Let be a nonempty closed bounded convex subset of a real uniformly convex Banach space U which satisfies the Opial’s condition [], and a b-enriched nonexpansive mapping with If is a sequence defined by , then converges weakly to a fixed point of T.
Proof.
Let . Then exists. We prove that has a unique subsequential limit in Let a and b be two weak limits of the subsequences and of respectively. As, and is demiclosed with respect to zero, where , by Lemma 2 we obtain that . Similarly, we can show that From Lemma 4, exists. Next, we prove the uniqueness. If , then by the Opial’s condition, we have
a contradiction, so and hence converges weakly to a fixed point of . □
Theorem 6.
Let be a nonempty closed bounded convex subset of a uniformly convex Banach space U and a b-enriched nonexpansive mapping. If is a sequence defined by and then converges to a point in if and only if or , where
Proof.
Necessity is obvious.
Conversely, Since , so .
Suppose that As proved in Lemma 5, exists for all by the given assumption we have therefore We now show that is a Cauchy sequence in As for given there is such that for all we have
which implies that
In particular, . Hence there exists such that
Now, for
This shows that is a Cauchy sequence in . As is closed and bounded subset of the Banach space U, there exists a point such that Now, gives that
□
Sentor and Dotson [] introduced the notion of mapping satisfying Condition (I) which is given as follows:
Definition 4.
A mapping is said to satisfy Condition (I), if there is a nondecreasing function with and such that
for all where .
We now prove a strong convergence result by using the Condition (I).
Theorem 7.
Let be a nonempty closed bounded convex subset of a uniformly convex Banach space U and a b-enriched nonexpansive mapping. Let be a sequence defined by and . If satisfies Condition (I) for the value of , then converges strongly to a fixed point of T.
Proof.
We proved in Lemma 5 that
From condition (I), we get
That is, . Since, is a nondecreasing function with and , we have . By Theorem 6, the sequence converges strongly to a point in . □
4. Application: Solution of Delay Fractional Differential Equations
In 1967, Caputo proposed a new form of fractional differentiation called Caputo’s fractional derivatives, which is defined as:
Under natural conditions on the function , for the Caputo derivative becomes a conventional n-th derivative of the function The main advantage of Caputo’s approach is that the initial conditions for fractional differential equations with Caputo derivatives take on the same form as for integer-order differential equations, i.e., contain the limit value of integer-order derivatives of unknown functions at the lower terminal
In 2017, Cong and Tuan [] obtained the existence and uniqueness of global solution of delay fractional differential equations by using properties of Mittag–Leffler functions and BCP. Many authors have solved the delay differential equations of fractional order using different approaches. For more details, we refer to [,,,,].
Here, we estimate the solution of a delay fractional differential equation [] by using an iterative scheme with Let be any constant and be a continuous mapping.
Consider the following delay Caputo fractional differential equation
with initial condition
where is continuous, and Suppose that the following conditions are fulfilled.
- f satisfies the Lipschitz condition with respect to 2nd and 3rd variables: That is, there exists a positive constant (depending on f) such thatfor all and
- There exists a positive constant depending upon L such that , that is,
A function is called solution of the initial value problem if it satisfies and .
It is known that [] finding the solution of and is equivalent to finding the solution of the following integral equation
with , Define a norm on by
where is a Mittag–Leffler function defined as:
Note that is a Banach space.
Wang et al. [] proved the existence and uniqueness of solution of delay differential Equations and provided that the condition holds. In the following theorem, we obtain an approximation of the solution using an iterative scheme for
Theorem 8.
Let ρ and f be functions as given above. If the conditions () and are satisfied, then the problem and has a unique solution and the sequence defined by converges to .
Proof.
The existence of unique solution is followed from []. Let be a sequence of defined by . Define an operator on by:
We now prove that as .
For it is easy to see that as .
Now, if , then using the proposed iterative process and conditions and we obtain
Taking supremum over on both sides of the above inequality, we have
Dividing by on both sides of the above equality, we obtain
As , we obtain
Let . Then by following similar arguments to those given above, we have
Thus,
Taking supremum over and dividing by on both sides of the above inequality, we obtain
Again by , we obtain
So,
Similarly,
If we set, , then we have
Thus is a monotone decreasing sequence of positive real numbers. Further, it is bounded sequence, we obtain
So,
□
5. Conclusions
In this paper we approximate the fixed point of -enriched contraction mapping by using a new iterative scheme (define by Abbas and Asghar) in the frame work of Banach spaces. It is also proved that the proposed iterative scheme is stable and converges faster than Picard, Mann, Ishikawa, Noor, Agarwal, Abbas, Thakur, M-iteration and F-iteration. We presented some numerical examples to support our claim. Further, we proved some strong and weak convergence results for b-enriched nonexpansive mapping in uniformly convex Banach space. In the end, using our proposed iterative scheme we approximated the solution of delay fractional differential equations.
Author Contributions
Conceptualization, M.A. and M.W.A.; methodology, M.W.A.; validation, M.A., M.W.A. and M.D.l.S.; formal analysis, M.W.A.; investigation, M.A. and M.W.A.; writing—original draft preparation, M.W.A.; writing—review and editing, M.A. and M.W.A.; supervision, M.A. and M.D.l.S.; project administration, M.D.l.S.; funding acquisition, M.D.l.S. All authors have read and agreed to the published version of the manuscript.
Funding
The authors are very grateful to the Basque Government for their support through Grant no. IT1207-19.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
Authors are thankful to the reviewers and editor for their constructive comments which helped us a lot in improving the presentation of the paper.
Conflicts of Interest
The authors declare no conflict of interest.
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