1. Introduction
The core of mathematics is to generalize concepts and results. Therefore, in the proposed research our aim is to generalize some classical and celebrated inequalities including Jensen’s inequality, Chebysev’s inequality, Andersson’s inequality, Slater’s inequality etc. For this purpose, we will use the notion of similarly separable vectors in separable Hilbert spaces. This notion of similarly separable vectors (sequences) was introduced by Marek Niezgoda in [
1]. This concept is a natural generalization of monotone sequences and synchronous sequences. It plays a central role in proving a class of linear inequalities, such as Chebyshev’s inequality and Andersson’s inequality.
We begin by recalling the basic integral inequalities for convex functions. Throughout this article, I and are intervals in .
We recall the integral version of Jensen’s inequality for convex functions [
2], p. 58. It relates the value of the integral of a convex function to that of a convex function of the integral.
Proposition 1. Let be a continuous function. If is a nondecreasing, bounded function and ; then, the inequalityholds for every continuous convex function . Steffensen presented a generalized form of Jensen’s Integral inequality, which we refer to as Jensen–Steffensen’s integral inequality [
2], p. 59. This may be stated as:
Proposition 2. Assume φ is continuous or has bounded variation and satisfies , and f is continuous and monotonic. Then inequality (1) holds. For other variants and related generalized results of the topic, we refer the reader to [
1,
3,
4,
5,
6,
7,
8].
Separable Hilbert Spaces
In this article, we take
U as an open subset in a separable Hilbert space
H, with a suitable inner product denoted by
. It is a known fact that every separable Hilbert space has a countable orthonormal basis [
9]. Separable Hilbert spaces possess many interesting properties ([
9,
10]).
Here, we recall some definitions from [
7]: let
be an ordered basis of
H and
the dual basis of
H. For
, we have
(Kronecker delta), where
(the dimensions of
H can be finite or infinite). We define Kronecker delta:
In this article, we will be using definitions of
-positive,
-separable, and
v-separable vectors as stated below [
7]. Additionally, throughout this chapter we assume
and
are index sets with
.
Definition 1. A vector is positive if ∀ i where .
We denote . And where and be two sets of indices.
Definition 2. Given and , a vector is separable w.r.t. a basis Ξ on and , if for and for .
Definition 3. A vector is v-separable w.r.t. Ξ on and , if z is separable on and for some .
Definition 4. A map preserves separability on and w.r.t. Ξ, if is separable on and w.r.t. Ξ given that is separable on and w.r.t. Ξ.
Definition 5. Let f, g, v, y and λ, . The vectors f, v are said to be similarly separable w.r.t. () if:
- (i)
f is separable w.r.t. Ξ on and ,
- (ii)
v is separable w.r.t. Θ on and .
This article consists of primarily three sections. In first section, we recall the basic definitions and previously proven inequalities. It also provides some basic notions related to similarly separable vectors.
Section 2 presents some important results, which include the integral version of Niezgoda’s inequality for similarly separable vectors in Hilbert spaces.
Section 3 follows by providing a refinement of our main result, which we proved in
Section 2.
Section 4 includes some applications, where we define and compare different means by making use of our refined inequality.
2. Generalization of Niezgoda’s Inequality
In this section, we generalize Niezgoda’s Inequality using Similarly Separable Vectors in Separable Hilbert Spaces. For that purpose, we recall Theorem 3.5 of [
1]:
Proposition 3. Take Ξ as a basis of H with inner product defined as , let Θ is the dual basis of Ξ. Let , and y be vectors in H. Denote , where . Under these conditions, the following are equivalent:
- (i)
The vector g is separable w.r.t. Θ on and if (or w.r.t. Θ on and if ).
- (ii)
The inequalityholds ∀
vectors f which are separable w.r.t. Ξ
on and .
Remark 1. This result has many important consequences as stated by Niezgoda in [1]. Niezgoda chose where for some fixed and standard inner product in Proposition 3 and stated all the related results and corollaries for the discrete version in [1]. Here, we are interested in its integral version. Consider a measure space
. Let
be a measurable function with
on a set of nonzero measure. We define the
weighted
space as
, where
means the measure
M defined by
and
. The inner product for
is
Corollary 1. Let , and y be vectors in . Denote where . Assume that Ξ is a basis of and Θ is the dual basis of Ξ.
If
- (i)
f is separable w.r.t. Ξ on and and
- (ii)
g is -separable w.r.t. Θ on and ,
Remark 2. Take and in (4); then, using Lebesgue measure we obtain the well-known Čebyšev inequality [2], p. 197: Corollary 2. Let s.t f and g are monotonic in the same direction. Let be an integrable function. Thenif the integrals exist. The reverse inequality (5) holds if g and f are monotonic in opposite directions. Equality in (5) holds in either cases iff either one of g or f is constant a.e. Remark 3. The inequality (5) still hold under different assumptions. For detailed discussion on inequality (5), we refer [2], pp. 198–199. Now, we recall a few important results from [
11] as under:
Proposition 4. A linear functional ϝ in a normed linear space with domain is continuous if and only if ϝ is bounded.
We now state the “Riesz Representation Theorem” [
11].
Proposition 5. For each linear functional ϝ that is bounded on a Hilbert space H, there is an inner product representation written as:where υ depends upon ϝ and has a unique value. The norm of υ is: If
U is an open convex subset in
V where
V is a normed linear space, then a convex function
on
U generates a supporting hyperplane at every point
[
12], p. 128. This implies the presence of a linear functional
that is continuous on
V and is characterized as
The functionals are known as the support of at , and the subdifferential of at the point is established through the set of all functionals .
Now, we consider Hilbert spaces: if
V is a Hilbert space, then the continuous linear functional
as defined in (
7) would be bounded by Proposition 4 and hence we fulfill all the requirements of Proposition 5. Bringing in use the Riesz representation theorem, we have a unique representation of all such functionals
as
for
such that
.
In this case inequality, (
7) becomes
The set of all such vectors (termed subgradients) constitute the subdifferential .
When
V is in
, the inequality (
8) becomes
where
for
and the set of all functions
(usually called subgradients) constitute of the subdifferential
(see, e.g., [
12,
13]).
We now present our first result:
Theorem 1. Consider an open subset U of H. Let be a convex function defined on U. Let be the subdifferential of ψ and let . Assume that Ξ is a basis of H with inner product and Θ is the dual basis of Ξ. Denote where , and y are vectors in H with . If
- (i)
f is separable w.r.t. Ξ on and ,
- (ii)
is separable w.r.t. Θ on and and
- (iii)
Φ preserves separability w.r.t. Ξ on and .
- (a)
If , thenholds. - (b)
If and then inequality (10) holds.
Proof. - (a)
Using the definition of subdifferential, we have:
Consider conditions
and
, we note that the vector
is
separable w.r.t.
on
and
. Using Proposition 3, we get
since
. So, if
, then (
10) follows from (
11) and (
12).
- (b)
Clearly, (
10) holds whenever
and
by using inequalities (
11) and (
12).
☐
Remark 4. Theorem 2.2 of [8] becomes a special case of our result by choosing with weighted inner product on for positive real weights and defined as:Additionally, we can easily obtain its corollaries and examples. Here, we are interested in one of its consequences in integral version. Remark 5. In Theorem 1, by choosing with inner product as defined in (3), we get the following integral majorization inequality: Corollary 3. Consider an open interval I of and let be a convex function, and be the subdifferential of ψ and .
Let be a measure space with positive finite measure η, and be two functions s.t. , where w be a non-negative measurable function on with on a set of nonzero measure.
Assume that Ξ
is an ordered basis in and Θ
is the dual basis of Ξ
. Let v and y be vectors in and the inner product is given by (3). Denote with . If - (i)
f is separable w.r.t. Ξ on and ,
- (ii)
is separable w.r.t. Θ on and and
- (iii)
Φ preserves separability w.r.t. Ξ on and .
Then:
- (a)
If , thenholds. - (b)
If and then inequality (14) holds.
Let us introduce some notations here that will be used in our next result. We denote this set of assumptions by .
: , and where is a partition of the interval .
We now present our main result:
Theorem 2. Consider an open interval and let be a convex function. Let be the subdifferential of ψ and let . Let and be two measure space with positive finite measures η and μ, respectively. Let and be two functions s.t. , where w is a non-negative measurable function on with on set of measure nonzero. Moreover, suppose the conditions in hold true. Further, we assume that Ξ, Θ,
y, and v are as in Theorem 1 and the inner product is given by (3). Denote for with . If - (i)
is separable w.r.t. Ξ on and ,
- (ii)
is separable w.r.t. Θ on and ,
- (iii)
,
- (iv)
Φ preserves separability w.r.t. Ξ on and ,
- (v)
∀ where γ is a non-zero constant,
thenholds, where . Proof. For
, by (
iii) we have
Using the aforementioned conditions, it follows from Corollary 3 that the following inequality holds for each
Additionally, we consider the fact that, since
for each
, we have
Now, we consider the L.H.S. of inequality (
15). Applying Integral Jensen’s inequality twice and using the aforementioned fact with inequality (
16), we get
☐
The discrete version similar to the above inequality (
15) was discussed in [
14], which is stated below.
Corollary 4. Consider an open interval and define to be a convex function.. Let be the subdifferential of ψ and . Suppose and is an matrix s.t. and is a monotonic m-tuple . Let s.t. . For each , if
- (i)
is -separable w.r.t. Ξ on and ,
- (ii)
is -separable w.r.t. Θ on and ,
- (iii)
,
- (iv)
Φ preserves -separability w.r.t. Ξ on and .
Thenholds, where with for and are a real tuple s.t. represents the weights and satisfies the condition
where
and
.
Remark 6. In Corollary 4, if we simply put and further consider the case of positive real weights , then we will get Niezgoda’s result as stated in Theorem 3.1 of [7]. 4. Applications to Integral Means
Using the integral form of Jensen’s Inequality, Haluska and Hutník introduced a class of generalized weighted quasi-arithmetic means in the integral form
[
16]. They used the definition suggested by F. Qi of quasi-arithmetic non-symmetrical weighted mean [
17] stated below.
Let where . Denote the vector space of all real Lebesgue measurable functions defined on by , and the classical Lebesgue measure and denote the positive cone of . Let denote the finite -norm of a function w.
Definition 6. Let and be a real continuous and strictly monotone function. The generalized weighted quasi-arithmetic mean of a function f with respect to weight function w is a number wherewhere denotes the inverse to the function g. Means include various two variable integral means frequently used as special cases when considering the suitable function w, f and g. For instance:
- (a)
Weighted Arithmetic Mean: For the identity function
, we obtain
- (b)
Weighted Harmonic Mean: for
, we have
- (c)
Weighted Power Mean of order r: for
, we obtain
When , we get the weighted geometric mean.
Using the assumptions of Theorem 2 where , we define the following notations. Denote .
We assume that and have the natural domain.
Using assumptions and refinement from Theorem 3, we obtain relationships between the following means:
- 1.
Arithmetic and Geometric mean:
Theorem 4. Under the assumptions of Theorem 3 we have Proof. In (
19), let
to obtain
Using our defined notations, we have
Using the porperty of
gives us,
☐
- 2.
Geometric and Harmonic mean:
Theorem 5. Under the assumptions of Theorem 3 we have Proof. In (
19) replace
and
and take
to get
Using our defined notations, we have
Multiplying the last inequality by (ln) (exp), we obtain
Using the property of
we have,
On simplification, we obtain
☐
- 3.
Power Mean and Arithmetic mean:
Theorem 6. Let all the assumptions of Theorem 3 be valid.
- (i)
- (ii)
The above inequalities are reversed in case .
Proof. - (i)
In (
19), replace
and
and take
, to obtain
Using our defined notations, we have
- (ii)
Incase
, the inequalities in (
21) are reversed since
is concave. ☐
5. Conclusions and Future Ideas
Marek Niezgoda stated all the results in n-dimensional real spaces (finite dimensional Hilbert spaces). We extended the idea by using separable Hilbert spaces, covering both the case of the finite dimensional and infinite dimensional, thus providing generalized integral results related to majorization, Niezgoda, and Ćebysév type inequalities. More concretely, using a concept of similarly separable vectors, Niezgoda stated all the results for the sequences, i.e., he provided discrete inequalities. We stated these results for functions taken from weighted spaces, i.e., we provided these results for integral inequalities. We also provided some refinements of these inequalities. Our proved inequalities are directly related to the Arithmetic, Geometric, Harmonic, and Power Means.
In the future, we can also provide a generalization of Mercer’s inequality [
6] using functions with non-decreasing increments. These results will be the generalization of results stated in [
18].
Additionally, we can further extend all the stated results by using the Isotonic Linear Functional [
2] and hence as an application we may state relations between some generalized means as given in [
15].