1. Introduction
Fuzzy sets theory has its origins in the paper published by Lotfi A. Zadeh in 1965 [
1]. At that time, the paper raised many discussions and was regarded as controversial, but it is nowadays considered the foundation of fuzzy logic theory and has reached over 100,000 citations. The concept of fuzzy sets has applications in many domains of the modern technological world. The importance of the fuzzy set notion and certain steps in the evolution of the concept are nicely highlighted in certain review papers [
2,
3], and the development of different areas of research due to this concept is now obvious.
The basis of fuzzy differential subordination theory was set in 2011 with the use of fuzzy set notion in introducing a generalization of the classical concept of subordination familiar to geometric function theory, called fuzzy subordination [
4]. Fuzzy subordination was then extended to fuzzy differential subordination in 2012 [
5]. It is seen as a generalization of the differential subordination concept introduced by S.S. Miller and P.T. Mocanu [
6,
7], developed by many researchers in the following years and synthesized in [
8]. The theory of fuzzy differential subordination developed by providing means for obtaining the dominants and best dominants of the fuzzy differential subordinations [
9] and by adding operators to the research [
10,
11,
12], continually following the general theory of differential subordination established in geometric function theory. The dual concept of fuzzy differential superordination was also introduced in 2017 [
13] and investigations relating the two concepts continued to provide new results [
14,
15].
The study of fuzzy differential subordinations continues and interesting results were recently published concerning a Mittag-Leffler-type Borel distribution [
16], connecting fuzzy differential subordination to different types of operators [
17,
18] or for obtaining univalence criteria [
19].
Fractional calculus had a powerful impact in recent research, having many applications in different branches of science and engineering. Its importance has been nicely highlighted in a recent review paper [
20]. A fractional integral is an important tool for obtaining new, interesting results. Recent papers present new integral inequalities obtained by applying fractional integrals and considering convexity properties [
21,
22], new extensions involving fractional integrals and the Mittag-Leffler Confluent Hypergeometric Function [
23] or tying it to other operators [
24,
25].
The tremendous development of fractional calculus during the last years also made an impression on the study regarding fuzzy differential subordination theory. New fuzzy differential subordinations were obtained using the Atangana–Baleanu fractional integral [
26], the fractional integral of the confluent hypergeometric function [
27] and the fractional integral of the Gaussian hypergeometric function [
28].
The research presented in this paper involves the fractional integral of the confluent hypergeometric function defined in [
29] and is investigated there using the means of classical theories of differential subordination and superordination. Considering the previous applications of this function in obtaining fuzzy differential subordinations and superordinations [
30], we continue the study and new fuzzy differential subordinations are obtained in this paper. The best fuzzy dominant is determined for each of them in the two theorems proved in the Main Results part of the paper. As a novelty, the conditions for the univalence of the fractional integral of the confluent hypergeometric function are stated using fuzzy differential subordinations. The first univalence result designed as the corollary of the first original theorem of this paper is obtained by using a certain function as the fuzzy best dominant. Another condition for the univalence of the fractional integral of the confluent hypergeometric function is provided in the second original theorem proved in this paper. An example is constructed in order to illustrate some applications of the newly proved theoretical results.
2. Preliminary Notions and Results
Certain notions specific to geometric function theory are implemented in this study.
Considering as the unit disc of the complex plane, the closed unit disc is denoted by and
Let denote the class of holomorphic functions in the unit disc. An important subclass of is defined as with .
For , the subclass of the functions denoted by consists of functions which can be written as
Let
be the class of the univalent functions in the unit disc and let
denote the class of the convex functions in the unit disc.
The following notions give the general context of fuzzy differential subordination theory established in [
4].
Definition 1 ([
4])
. A pair , where and is called the fuzzy subset of . The set is called the support of the fuzzy set and is called the membership function of the fuzzy set One can also denote .
Definition 2 ([
4,
5])
. Let and let be a fixed point and let the functions be holomorphic in The function is said to be a fuzzy subordinate to function and write or if there exists a function such that:- (i)
- (ii)
Remark 1. - (a)
- (b)
Relationis equivalent toand
- (c)
If, then relations andare equivalent to - (d)
Such functions
can be considered:
Definition 3 ([
5])
. Let and let be univalent in with and Let be univalent in with and let be analytic in with Function is also analytic in and let . If satisfies the (second-order) fuzzy differential subordinationthen
is called the fuzzy solution of the fuzzy differential subordination. The univalent function
is called the fuzzy dominant of the fuzzy solutions of the fuzzy differential subordination, or more simply a fuzzy dominant, if
for all
satisfying (1). A fuzzy dominant
that satisfies
for all fuzzy dominants
of (1) is said to be fuzzy best dominant of (1). The next notions are tools of the classical theory of differential subordination.
Definition 4 ([
3])
. We denote by the set of functions that are analytic and injective on whereand are such that for Definition 5 ([
3])
. Let be a set in , and let be a positive integer. The class of admissible functions consists of functions that satisfy the admissibility conditionwheneverThe set
is called the class of admissible functions and condition (2) is called the admissibility condition.
If, then the admissibility condition (2) reduces towhenever Remark 2. - (a)
In the special case whenis a simply connected domain, andis a conformal mapping ofinto, the class of admissible functions is denoted byor.
- (b)
In the particular case whenandthe class of admissible functions is denoted bySince, when,, the admissibility condition (2) becomes:whenever In the particular case whenthe admissibility condition (4) becomes:whenever
One of the first papers where the confluent hypergeometric function was used for research in geometric function theory appeared in 1990 [
31] and involved univalence conditions for this function. The confluent hypergeometric function is defined as:
Definition 6 ([
31])
. Let a and c be complex numbers with and considerThis function is called the confluent (Kummer) hypergeometric function, is analytic inand satisfies Kummer’s differential equation: If we letthen (6) can be written in the form Euler’s Gamma function is defined for
as:
The gamma function satisfies:
The fractional integral of the confluent hypergeometric function is defined in [
29] as follows:
Definition 7 ([
29])
. Let a and c be complex numbers with and let We define the fractional integral of the confluent hypergeometric functionWe note thatForwe can write: We obtain, In order to prove the original results contained in the next section, we need the following already-established results.
Lemma 1 ([
8])
. Let with and let be analytic in with and If is not subordinate to , then there exists points and and an for which and:
- (i)
- (ii)
- (iii)
Lemma 2 ([
8])
. Let If , then 3. Main Results
The first theorem investigates a new fuzzy differential subordination involving the fractional integral of the confluent hypergeometric function. The best dominant of the subordiantion is found and this result will be used for stating a condition for the univalence of the fractional integral of the confluent hypergeometric function in the corollary which follows the theorem.
Theorem 1. Letbe a univalent solution of the equation Functionis convex in. Letbe given by:
Let the confluent hypergeometric functionbe given by (6) and the fractional integral of the confluent hypergeometric functionbe given by (8).
If the following fuzzy differential subordination is satisfied written equivalently asorthen the fuzzy differential subordination implieswritten equivalently as or This functionis the best fuzzy dominant.
Using the expression of the fractional integral of the confluent hypergeometric function given by (8), we can write:
hence,
By differentiating relation (13), after some simple calculations, we obtain:
We let the function
be given by:
For
relation (15) becomes:
Using relation (16) in (14), we obtain:
Using (17), fuzzy differential subordination (12) becomes:
Using Definition 2 and Remark 1, we write:
For
relation (19) is written as:
It is now time to use Lemma 1 and the admissibility condition (3).
Assume that the functions satisfy the conditions required by Lemma 1 in the closed unit disc If this is not true, the functions and can be replaced by and , respectively, which are functions that have the desired properties.
Additionally, assume that
Then, by applying Lemma 1, we get that there exist points
and
and an
such that
Using these conditions with
in Definition 5 and considering the admissibility condition (3), we write:
On the other hand,
and we can write
Using (22) in (21), we obtain:
Relation (23) contradicts the assumption made when writing relation (20) and we conclude that the assumption is false, hence
Using relation (8) in (24), we have:
Since function is a univalent solution of Equation (10), we get that function is the best fuzzy dominant. □
The following corollary can be obtained by using the convex function as the best fuzzy dominant in Theorem 1. As a result, a condition for the univalence of the fractional integral of the confluent hypergeometric function is stated.
Corollary 1. Let functionbe a univalent solution of the equation Functionis convex in.
Letbe given by: Let the confluent hypergeometric functionbe given by (6) and the fractional integral of the confluent hypergeometric functionbe given by (8).
If the following fuzzy differential subordination is satisfiedwritten equivalently asor then the fuzzy differential subordination implies: written equivalently asor with functionbeing the best fuzzy dominant, and also, written equivalently, Proof. First, we prove that function
is convex in U. In order to achieve that conclusion, we calculate:
We now prove that function
is a solution of Equation (26).
We now prove that function
is univalent in
For that we calculate:
since
Relation (29) states that function is a convex function in
We also prove that function is convex in
Using relation (29), we get that
Hence, function
is a convex function in
Using relation (24) from the proof of Theorem 1, for
we obtain:
Since function a univalent solution of Equation (26), we conclude that is the best fuzzy dominant.
Considering the fact that function
is a convex function, fuzzy differential subordination (30) is equivalent to
Because function is univalent in , it is a conformal mapping of the unit disc into the half-plane and we conclude that
We can now state that
which is equivalent to
□
The next theorem gives a sufficient condition for the univalence of the fractional integral of the confluent hypergeometric function given by (9).
Theorem 2. Letbe a univalent solution of the equation Letbe a convex function inwithLetbe given by: Let the confluent hypergeometric functionbe given by (6) and the fractional integral of the confluent hypergeometric functionbe given by (9).
The fuzzy differential subordinationimplies:
- (a)
whereis the best fuzzy dominant.
- (b)
Proof. We first prove part of the theorem.
We have that
For finalizing the proof, Lemma 1 and Definition 5 will be applied.
Let
be given by
For
relation (32) becomes:
Using (37), the fuzzy differential subordination (34) becomes:
Since
is a convex function,
is a convex domain and fuzzy differential subordination (38) can be written equivalently as:
For
relation (39) becomes:
We shall assume that
Then, by applying Lemma 1, we get that there exists points
and
and an
such that
By replacing
in admissibility condition (2), we have:
from where we deduce
Since relation (42) contradicts relation (40), we conclude that the assumption we have made is false, hence
Using relation (35) in (43), we write:
Since is the univalent solution of Equation (32), we have that function is the best fuzzy dominant.
Since and in order to prove part b), it suffices to prove that function given by (36) satisfies For that, we check the admissibility condition (5).
For
,
,
, the admissibility condition
(5) becomes:
which is equivalent to
Using the conditions
and
by applying Lemma 2, we get that
By replacing, in (46), the expression of the function
given by (35), we obtain:
Since and using (47), we conclude that function is univalent in □
Example 1. We havehence,
is a convex function in Then, we get:
hence,
is a convex function in.
Letthen, we have the fractional integral of the confluent hypergeometric function:
Using Theorem 1, we write:
Letbe the univalent solution of the equation Functionis convex inLetbe given by: If the following fuzzy differential subordination is satisfiedwherewritten equivalently as orthen it implies:
written equivalently as or Indeed, sinceis a convex function, the fuzzy differential subordination is equivalent to writing: Functionbeing univalent, we know that it represents a conformal transform of the unit discinto the half-planehence, we have:equivalently written as the inclusion of sets:
If we letthen we haveandwhich, according to Definition 2 means that: