1. Introduction
The convexity of functions has been a continual research topic. Many mathematicians have devoted themselves to introducing different forms of convexity such as
r-convex,
m-convex, quasi-convex, etc. (see [
1]). At the same time, as a generalization of convexity on
, a few researchers have studied the convexity on different sets. In [
2], Atıcı and Yaldız defined the convexity of a real function on any time scale
.
The convexity for a real function
f on
means that for any
with
,
where
and
. Obviously, for
, the convex function
f on
reduces to an ordinary convex function.
As an important direction for the theory of convex analysis, the Hermite-Hadamard (H-H) inequality has attracted much attention and has been generalized to many forms in recent decades (see, e.g., [
3,
4]). The classical H-H inequality is stated as follows: Let
f be a real convex function defined on
, where
. Then
The H-H inequality also plays a meaningful role in fractional calculus. For instance, in [
5], Sarikaya et al. first established the H-H inequality for Riemann-Liouville fractional integral operators: Let
be a convex function; then, for
,
In [
6], Sarikaya et al. proposed an alternative form to the H-H inequalities for Riemann-Liouville fractional integral operators based on the midpoint of
a and
b: Assume
f is a convex function defined on
; then, for
,
In 2021, Fernandez and Mohammed [
7] proved the H-H inequality relating to Atangana-Baleanu fractional operators defined using Mittag-Leffler kernels. Later, Sahoo et al. [
8] introduced the H-H inequalities related to
k-Riemann-Liouville fractional operators for different kinds of convex functions. For more recent results which generalize the classical H-H inequality via different fractional operators, we refer the reader to the papers [
9,
10,
11,
12,
13] and references therein.
On the other hand, the H-H inequality has been also extended to discrete calculus and even discrete fractional calculus. In [
2], Atıcı and Yaldız proved discrete H-H inequalities on
:
They also improved it to be discrete fractional H-H inequalities on
:
where
and
which can be seen as a discrete counterpart of (
1). Recently, Mohammed et al. [
14] proved some Hermite-Hadamard and Opial inequalities using the integration by parts and chain rule formulas on time scales. For more of the H-H inequalities on time scales, one can see [
15,
16,
17,
18,
19,
20,
21] and the references therein.
So far, the Hermite-Hadamard inequalities for the midpoint on the time scale have rarely been studied. The goal of this article is to prove the generalized H-H inequalities for discrete convex functions on
and
and establish two H-H inequalities involving the nabla fractional sum operators, as similar forms to discrete versions of (
2).
The whole study work has been arranged as follows: In
Section 2, we recall some basic definitions and theorems. In
Section 3, we establish some discrete H-H inequalities on the time scales
and
, respectively. In addition, they are extended to discrete fractional forms. Furthermore, there are two examples of the H-H inequalities in
Section 4. Finally, the conclusion of this paper is given in
Section 5.
2. Preliminaries
In this section, we recall some definitions and results used in the remaining sections. Let be any time scale. The sets considered in this article are , and . For , we write and to denote and , respectively.
For , we denote the forward jump and the backward jump operators by and , respectively. The forward graininess and the backward graininess operators are given by and , respectively. If , we denote and by and with , respectively. Let be a function defined on ; then, for and , , i.e., empty sums are taken to be 0.
Assume
t and
are arbitrary real numbers; then, the rising and falling
h-factorial functions are given by
and
where the gamma function is defined by
. In particular, for
, we obtain
,
.
Next, we recall the differences and sums of f on .
Definition 1. ([
22])
. Let real function f defined on be given. Then, for , the nabla and delta differences of f are given byThe nabla and delta sums of f on are given bywhere and . Especially for
, we have
where
.
Definition 2. (
The nabla h-fractional sums [23]).
Let real function f and be given. Then, the nabla left and right h-fractional sums are defined as Definition 3. (The delta
h-fractional sums [
24]).
Let real function f and be given. Then, the delta left and right h-fractional sums are defined as If , we denote , , and by , , and , respectively.
Remark 1. There is an equality between the delta right fractional sum and the nabla right fractional sum In fact,where we use that The following substitution rules on time scale are necessary for the proof of discrete H-H inequalities on .
Theorem 1. ([
22]).
Let be strictly increasing and differentiable with rd-continuous derivative. If is a time scale and is rd-continuous, then for ,where is derivative operator on the time scale . Theorem 2. ([
25]).
Let be strictly decreasing and differentiable with rd-continuous derivative. If is a time scale and is rd-continuous, then for where is derivative operator on the time scale . 3. Main Results
In this part, we construct and establish some generalized H-H inequalities for convex functions defined on and using two methods.
3.1. Generalized Hermite-Hadamard Inequalities on Discrete Time Scale
In this subsection, two generalized H-H inequalities on
are deduced by using the substitution rules shown in Theorem 1 and Theorem 2. Here, the notations are used:
and
First, we prove the discrete H-H inequalities on relating to the midpoint .
Theorem 3. Let with and defined on be a convex function. If , then we have Proof. Let
be fixed. We define
are in
and
. Since
f is convex on
, we can deduce
Integrating the above inequalities with respect to
over
, then we have
Here, we calculate and , separately.
Let
be defined by
with
. Then,
is decreasing:
Making use of Theorem 2, we obtain
Assume
with
. Setting
and
, we have
and
. Then
Let
be a map defined as
. Then,
is increasing:
Hence, using Theorem 1, we have
Inserting
and
into (
18), we obtain
which completes the proof of the theorem. □
Next, the above H-H inequalities are extended to discrete fractional forms involving the nabla h-fractional sums on .
Theorem 4. Let with and defined on be a convex function. If , then for , we havewhere Proof. Let
be fixed. We define
are in
and
. Since
f is convex on
, we can deduce
Multiplying each term by
and integrating with respect to
on
, then
that is,
where
Let
be defined as
with
. Then,
is decreasing:
In addition, let
and
. Then, we obtain
Making use of Theorem 2, we obtain
On the other hand, we assert that
Assume
for
. Setting
and
, we have
and
. Then
Let
be a map defined as
. Then,
is increasing:
In addition, we define
and
. Then, we obtain
Hence, using Theorem 1, we have
Thus, we obtain
proving the theorem. □
Remark 2. Note that, concerning the discrete fractional H-H inequalities on , we obtain
- 1.
For , Theorem 4 reduces to Theorem 3.
- 2.
From Remark 1, the following inequalities for the nabla left and delta right fractional sums are equivalent to inequalities (24):which can be seen as the midpoint type of the inequalities (3).
3.2. Generalized Hermite-Hadamard Inequalities on Discrete Time Scale
Here, we use the definitions of
h-sum operators to prove the discrete H-H inequalities on
. Denote
by
Theorem 5. Let with and defined on be a convex function. If , then inequalitieshold. Proof. Fix
with
. Suppose
then
and
. Due to the convexity of
f, we obtain
Setting
with
, then
and
Taking sum over
k from 1 to
, then
Next, we calculate and , separately.
For
, setting
, we obtain
For
, setting
, we obtain
Hence,
which are the desired inequalities. □
Remark 3. Note that the inequalities (36) with and deduce to the inequalities (15) in Theorem 3. The next result is important to prove the discrete fractional H-H inequalities on .
Lemma 1. Let a real function f be defined on and be given. Suppose , and . Then we obtainwhere . Proof. Using Definition 2, we can show that
Then, we set
to obtain
Thus, Lemma 1 is proved. □
From Lemma 1, the following theorem can be proved.
Theorem 6. Let with and defined on be a convex function. If , then for , the inequalitieshold, where Proof. Fix
with
. Suppose
then
and
. Due to the convexity of
f, we obtain
Setting
, then
and
Multiplying each term by
and taking sum over
k from 1 to
with
, we obtain
Setting
and
, we obtain
that is,
where
Then, with the help of Lemma 1, we can obtain
Thus, Theorem 6 is proved. □
Remark 4. It is worth noting that:
- 1.
In Theorem 6, when and , the inequalities (46) are consistent with the inequalities (24) of Theorem 4:where In fact, using the time scale substitution rule (see Theorem 2), we havewhere and . - 2.
If we take , then the inequalities (46) of Theorem 6 are consistent with the inequalities (36) of Theorem 5.
4. Examples
In this section, we give two examples to illustrate our results.
Example 1. Let be defined as , where and . Obviously, f is a convex function. Hence, we have Example 2. Let be defined as , where and . Due to the convexity of f, then the following H-H inequalitieshold. Hence, we have Taking , then we obtain Note that if we take , thenwhere we use the fact that . 5. Conclusions
The H-H inequalities play a meaningful role in mathematics, and they have been generalized to different forms. However, inequalities for the convex function defined on time scales are rarely studied. In this article, we established two types of discrete H-H inequalities on time scales: and , respectively. In addition, we proved two discrete fractional H-H inequalities for fractional sums. In the future, other generalized H-H inequalities, relying on different forms of convexity or sum operators, can be introduced by similar methods. Furthermore, the discrete H-H inequalities can be studied for the qualitative properties of difference equations.