1. Introduction
In recent years increasing research attention has been devoted to the study of discrete fractional calculus (DFC) and its various models. Moreover, DFC has been suitably characterized the term “memory” especially in physics, economics, mathematics, biology, engineering, control etc., and its study is not only interesting from a purely mathematical point of view, but has been found extremely useful for modeling super-diffusion processes, which naturally appear in many applications in biology, probability, physics, economics, medicine and ecology (see [
1,
2,
3,
4]). Additionally, there are some recent works on variable-order fractional difference equations such as [
5,
6,
7,
8,
9,
10] in discrete fractional calculus.
Recently, several authors have begun to study monotonicity analysis in the context of discrete fractional calculus, especially in fractional difference equations. They have often obtained some
-increasing and
-decreasing results for the discrete nabla and delta operators. Additionally, there are many discrete models that have been studied in their research articles. Atici and Uyanik [
11] obtained several monotonicity analysis results for the discrete nabla Riemann–Liouville fractional operators on the time scale
. Moreover, Suwan et al. [
12] obtained some new results for the discrete delta Riemann–Liouville fractional operators on the time scale
. For the discrete nabla Attangana–Baleanu fractional operators, several monotonicity analysis results were obtained by Abdeljawad and Baleanu [
13] on the time scale
, and Suwan et al. [
14] on the time scale
. Abdeljawad and Abdallaa [
15] used the dual identities to obtain some monotonicity results for the discrete nabla and delta Riemann–Liouville and Caputo fractional operators on the time scale
. Goodrich et al. [
16] obtained some analysis results including monotonicity for the discrete fractional operators with exponential kernels. Recently, Mohammed et al. [
17] established new monotonicity results for discrete generalized nabla Attangana–Baleanu fractional operators with discrete generalized Mittag–Leffler kernels on the time scale
.
Motivated by the article [
18], this article is devoted to a detailed study of discrete delta Caputo–Fabrizio (CF) fractional operators, the associated monotonicity analysis of the operators, related concepts such as the discrete delta Laplace transform method, the relationship between the Riemann and Caputo operators, and fractional difference mean value theorem. However, Abdeljawad and Baleanu [
18] have established different results for discrete nabla CF fractional operators due to the difference in the kernels of discrete delta and nabla CF fractional operators; however, their results are not in detail.
Specifically, the structure of this article is as follows. We discuss the discrete delta CF fractional differences in
Section 2. We derive the discrete delta CF fractional sums and we present some related properties in
Section 3, then pass to monotonicity analysis of the discrete delta operators in
Section 4, first discrete delta Caputo-Fabrizio-Caputo (CFC) operators and then discrete delta Caputo-Fabrizio-Riemann (CFR) operators. In
Section 5, we investigate the discrete fractional difference Mean Value Theorem (MVT) based on the monotonicity results.
Section 6 is devoted to discussion and conclusion of our article.
2. Preliminaries and Basic Concepts
We first indicate the definitions of the discrete delta CF fractional operators that we will consider in this article.
Definition 1 (see [
19])
. Let and . Let be the forward difference operator and be the backward difference operator. Then, for any function ρ defined on , the left discrete delta CFC and CFR fractional differences are, respectively, defined byAdditionally, for any function ρ defined on , the right discrete delta CFC and CFR fractional differences are, respectively, defined by where a normalizing positive constant satisfying .
Remark 1. By comparing Definition 1 and Definition 1 of [18], we can notice a few differences between the discrete delta and nabla CF fractional operators, e.g., their kernels. This and further differences in their properties confirm that our results in this article are quite different from those obtained in [18]. To see further differences, we advise readers to read both articles. Remark 2 (see [
19])
. From Definition 1, we can note the following limiting cases: Definition 2 (see [
20] [
operator action])
. Let ρ be defined on with and , then the operator action of ρ is used to connect the left and right fractional differences and sums, and it is defined by . In the following we apply the operator for the new fractional differences stated in Definition 1.
Proposition 1. For the fractional differences in Definition 1, one can obtain the following transformation:
- (i)
,
- (ii)
.
Proof. These follow immediately by applying the operator on the fractional differences in Definition 1 and using the fact that . □
It is of interest to recall the discrete delta Laplace transform.
Definition 3 (see [
1])
. The discrete delta Laplace transform for a function ρ defined on is defined by Definition 4 (see [
1])
. Let be two functions and . The discrete delta convolution transform of a function ρ with g is defined byMoreover, the discrete delta Laplace transform of is given by Lemma 1 (see [
1])
. For and , we haveIn particular, when , we have Lemma 2 (see [
1])
. For any function ρ defined on , we have 3. Discrete Delta Caputo–Fabrizio Fractional Sums
To derive the discrete delta CF fractional sums corresponding to the discrete delta CF fractional differences in Definition 1, we consider the delta fractional difference equation:
In the light of (
2) and (4), we can rewrite (
7) as follows:
Taking discrete Laplace transform on both sides of (
8), and then using (
6) and Lemma 2, we obtain
where
and
. It follows that
Taking inverse Laplace transforms on both sides, we obtain
This allows us to define the following discrete delta CF fractional sums.
Definition 5 (Left discrete delta Caputo–Fabrizio fractional sums)
. Let and ρ be defined on , then we define the left discrete delta CF fractional sum as follows: By applying the
operator on both sides of the fractional sum (
10), we obtain
Changing the variable
, it follows that
Thus, the following definition is valid.
Definition 6 (Right discrete delta Caputo–Fabrizio fractional sums)
. Let and ρ be defined on , then we define the right discrete delta CF fractional sum as follows: Proposition 2. For , we have
- (i)
and ,
- (ii)
and .
Proof. The proofs follow directly from Definitions 1, 5 and 6. □
The relationship between discrete delta CFC and CFR fractional differences are given in the following proposition:
Proposition 3. For , we have
- (i)
,
- (ii)
.
Proof. By taking the Laplace transform to (
1), we obtain
Taking inverse Laplace transforms and using Lemma 1, we obtain the result for the first item. The second item can be proved by applying the action of the operator on the first item. □
The following lemmas are essential in order to proceed.
Lemma 3. Let and , we have
- 1.
;
- 2.
;
- 3.
;
- 4.
;
- 5.
;
- 6.
.
Proof. Since the proof of items (2) and (4) are easy and direct, we only prove only prove the items (1), (3), (5), and (6) as follows.
- (1)
We use the definition (
10) for
to obtain
which is the desired result.
- (3)
Again, we use the definition (
10) for
to obtain
which is the required result.
- (5)
Here we use the definition (
2) for
and we obtain
which is the stated result.
- (6)
Definition (
2) with
leads to
which is the end of the proof. □
4. Results on Discrete Monotonicity Analysis
In this part, we focus on implementing monotonicity analysis for the discrete delta CF fractional operators.
Definition 7 (see [
11,
14,
15,
21])
. Let and be a function satisfying . Then, ρ is called an ν-increasing function on , ifand ρ is called an ν-decreasing function on , if Remark 3. Note that
If in Definition 7, then increasing and ν-increasing concepts coincide, and decreasing and ν-decreasing concepts coincide.
If is increasing on , then for all , and thus is ν-increasing on . Moreover, if is decreasing on , then for all , and thus is ν-decreasing on .
Remark 4. It should be noted that for each .
Theorem 1. If a function satisfies and for each and , then is –increasing.
Proof. Rewriting
as follows:
Now, based on the assumption, we have
We shall proceed by induction on
. First, by substituting
into (
13), we see that
. Again, by substituting
into (
13) yields
this implies that
. Assume that
Then, we will try to show that
. Use identity (
13) by replacing
by
to obtain
Thus, the result is proved. □
Theorem 2. If all notations given in Theorem 1 are satisfied and then is –increasing.
Proof. This follows immediately from Proposition 2 and Theorem 1. □
The following results are the decreasing analogues of Theorem 1 and Theorem 2, respectively.
Proposition 4. If a function satisfies and for each and , then is –decreasing.
Proposition 5. If a function satisfies and then is –decreasing.
Moreover, the following results are the strictly increasing (or strictly decreasing) analogues of Theorem 1 (or Proposition 4) and Theorem 2 (or Proposition 5), respectively.
Proposition 6. If a function satisfies and for each and , then is –strictly increasing , respectively.
Proposition 7. If a function satisfies and then is –strictly increasing , respectively.
Theorem 3. Let be a function with and increasing on . Then, we have Proof. The result will be proved if we can show that
is increasing on
, where
is as before. We proceed by induction on
. The
case of (
13) leads to
by assumption. Now let us assume the result is true for
, i.e.,
for each
such that
, and prove it for
, i.e.,
.
Considering the assumption,
is increasing on
, it follows that
Then, by using (
13) yields
It should be remarked that
since
is increasing on
. For each
, it follows that
where we use (
15), Remark 4 and the geometric series sum formula. Thus, we have shown that
is increasing as required. □
Theorem 4. With all notation given in Theorem 3, we have Proof. This is immediate from Proposition 2 and Theorem 3. □
The decreasing analogues of Theorem 3 and Theorem 4 are given in the following propositions, respectively.
Proposition 8. Let be a function with and decreasing on . Then, we have Proposition 9. Let be a function with and decreasing on . Then, we have Furthermore, the strictly increasing (or strictly decreasing) analogues of Theorem 3 (or Proposition 8) and Theorem 4 (or Proposition 9) are given in the following propositions, respectively.
Proposition 10. Let be a function with and strictly increasing on . Then, we have respectively.
Proposition 11. Let be a function with and strictly increasing on . Then, we have respectively.
5. Fractional Difference Mean Value Theorem
The monotonicity results of the previous section can be applied to reformulate the discrete fractional MVT. First, we recall that . However, the next result contains an initial condition and it will be a useful tool to obtain the discrete fractional difference MVT.
Proof. Using Definition 1 and Lemma 3, we have
Hence, the result. □
Corollary 1. Let g be a function defined on with and strictly increasing on . Then, for each , we have Proof. Since
g is strictly increasing and
, we know from Proposition 10 that
Applying
to the above inequality and using Theorem 5, we see that
Thus, we have proved the result as required. □
Theorem 6 (Fractional difference MVT for the CFR case).
Let ρ and g be two functions defined on such that g is strictly increasing and , and let and with , then, there exist with Proof. First, from Proposition 10 and Corollary 1, we can see that the denominators in (
17) are all positive. We proceed by contradiction. Suppose that (
17) is not true. Then, either
or
Considering Proposition 10, the inequality (
18) can be rewritten as
We apply the fractional sum operator
to both sides of the above inequality at
and use the (
16) to obtain
which is a contradiction. Analogously, inequality (
19) will lead to contradiction. Thus, the result is proved. □
In the next theorem, we give the result of as we did for the CFC case in Theorem 5.
Theorem 7. For , we have Proof. We begin using the relationship in Proposition 3:
By applying
to both sides of (
21), we have:
Using Theorem 5 and Lemma 3 (1), we have:
which is the end of the proof. □
Remark 5. As we have discussed in our recently published article [22], it is impossible to obtain fractional difference MVT for the CFC case, i.e., the following inequalities do not hold true. The main reason for this is that the discrete delta CFC fractional difference is not clear whether it is greater than zero or not by means of Proposition 11.
6. Conclusions
To obtain the mean value theorem with discrete fractional difference terms, monotonicity analysis is considered for the discrete delta Caputo–Fabrizio fractional operators. Before analysing the monotonicity results, the discrete delta Caputo–Fabrizio fractional differences are introduced and the discrete delta CF fractional sums are investigated on the time scale . Additionally, the discrete right operators are found by applying action of operator to the corresponding discrete left operators. Besides that, the discrete delta Laplace transform technique is applied to find a correlation between the discrete delta CFC and CFR fractional differences. We see that a function is -increasing, when and for and . Conversely, we see that for and for and , when the function is increasing on and . These results finally lead to obtaining the fractional difference mean value theorem.
Some of the ideas used in the current paper are similar to those for previously existing models of discrete fractional calculus with various singular- and nonsingular-type kernels; however, this is the first time that the discrete delta Caputo–Fabrizio fractional operators have been used in this way to construct fractional difference mean value theorem and monotonicity analysis. Previous contributions in this direction have included using discrete nabla Caputo–Fabrizio fractional operators to construct difference mean value theorem [
18], using discrete nabla Atangana-Baleanu fractional operators to construct difference mean value theorem [
13], and using discrete nabla Caputo and Riemann fractional operators to construct difference mean value theorem [
15].
In the future, researchers can extend the results of this paper by considering other types of discrete fractional calculus. The work here is set within the discrete delta Caputo–Fabrizio model, but it may be possible to extend it, applying the same arguments in some general class of discrete fractional operators, to obtain further results which would be useful in the direction of monotonicity analysis.
Author Contributions
Conceptualization, P.O.M. and T.A.; data curation, F.K.H.; formal analysis, P.O.M. and T.A.; funding acquisition, T.A.; investigation, P.O.M.; methodology, F.K.H.; project administration, P.O.M. and T.A.; software, P.O.M. and T.A.; supervision, T.A. and F.K.H.; validation, F.K.H.; visualization, F.K.H.; writing—original draft, P.O.M.; writing—review and editing, T.A. and F.K.H. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
The second author would like to thank Prince Sultan University for funding this work through research group Nonlinear Analysis Methods in Applied Mathematics (NAMAM) group number RG-DES-2017-01-17.
Conflicts of Interest
The authors declare no conflict of interest.
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