1. Introduction
The concept of fuzzy set, introduced by Lotfi A. Zadeh in 1965 [
1], has opened the way for a new theory called fuzzy set theory. It has developed intensely, nowadays having applications in many branches of science and technology.
The fuzzy set concept was applied for developing new directions of study in many mathematical theories. In geometric function theory, it was used for introducing the new concepts of fuzzy subordination [
2] and fuzzy differential subordinations [
3] as generalizations of the classical notion of differential subordination due to Miller and Mocanu [
4,
5]. The main aspects regarding the theory of differential subordination can be found in [
6]. Steps in the evolution of the theory of fuzzy differential subordination can be followed in [
7].
The general context of the study presented in this paper contains notions familiar to geometric function theory merged with fuzzy set theory. We first present the main classes of analytic functions involved and the definitions regarding fuzzy differential subordination theory.
represents the unit disc of the complex plane and the space of holomorphic functions in U.
Consider and for and .
We remember the usual definitions needed for fuzzy differential subordination:
Definition 1 ([
8])
. A fuzzy subset of X is a pair , with the support of the fuzzy set and the membership function of the fuzzy set. It is denoted . Remark 1. When , we have
Evidently , , and , .
Definition 2 ([
2])
. Let and let be a fixed point. We take the functions . The function f is said to be fuzzy subordinate to g and we write , if there exists a function such that and , Remark 2. (1) If g is univalent, then if and only if and
(2) Such a function can be consider ,
(3) If the conditions become and , which is equivalent to the classical definition of subordination.
Definition 3 ([
3])
. Consider h an univalent function in U and , such that . When the fuzzy differential subordinationis satisfied for an analytic function p in U, such that , then p is called a fuzzy solution of the fuzzy differential subordination. A fuzzy dominant of the fuzzy solutions of the fuzzy differential subordination is an univalent function q for which , , for all p satisfying (1). The fuzzy best dominant of (1) is a fuzzy dominant , such that , , for all fuzzy dominants q of (1). Lemma 1 ([
6])
. Consider . If , then is a convex function, . Lemma 2 ([
9])
. Consider a convex function h with , and such that . When , , is an analytic function in U andthenwith the convex function as the fuzzy best dominant. Lemma 3 ([
9])
. Consider a convex function g in U and define with and .If is a holomorphic function in U andthen we obtain the sharp result The original results exposed in this paper are obtained using the well-known Ruscheweyh and Sălăgean differential operators combined with Riemann–Liouville fractional integral. The resulting operator was introduced in [
10], where it was used for obtaining results involving classical differential subordination theory. The necessary definitions are reminded:
Definition 4 (Ruscheweyh [
11])
. The Ruscheweyh operator is introduced by ,for Remark 3. For a function the Ruscheweyh operator can be written using the following form , , where Γ denotes the gamma function.
Definition 5 (Sălăgean [
12])
. The Sălăgean operator is introduced by ,for , , Remark 4. For a function , the Sălăgean operator can be written using the following form , .
Definition 6 ([
13])
. Define the linear operator given bywhere , . Remark 5. For a function the defined operator can be written using the following form
We also remind the definition of Riemann–Liouville fractional integral:
Definition 7 ([
14])
. The Riemann–Liouville fractional integral of order λ applied to an analytic function f is defined bywith In [
10] we defined the Riemann–Liouville fractional integral applied to the operator
as follows:
Definition 8 ([
10])
. The Riemann–Liouville fractional integral applied to the differential operator is introduced bywhere , and . Remark 6. For a function the Riemann–Liouville fractional integral of has the following formand The results exposed in this paper follow a line of research concerned with fuzzy differential subordinations which is popular nowadays, namely introducing new operators and using them for defining and studying new fuzzy classes of functions.
Fuzzy differential subordinations involving Ruscheweyh and Sălăgean differential operators were obtained in many studies, such as [
15]. New operators introduced using fractional integral and applied in fuzzy differential subordination theory were studied in [
16] where Riemann–Liouville fractional integral is applied for Gaussian hypergeometric function and in [
17] where Riemann–Liouville fractional integral is combined with confluent hypergeometric function.
Motivated by the nice results obtained in fuzzy differential subordination theory using Ruscheweyh and Sălăgean differential operators and fractional integral applied to different known operators, the study presented in this paper uses the previously defined operator
given in Definition 8 applied for obtaining new fuzzy differential subordinations. In the next section, a new fuzzy class will be defined and studied in order to obtain fuzzy differential subordinations inspired by recently published studies concerned with the same topic seen in [
18,
19,
20].
The main results contained in
Section 2 of the paper, begin with the definition of a new fuzzy class
for which the operator
given in Definition 8 is used. The property of this class to be convex is proved and certain fuzzy differential subordinations involving functions from the class and the operator
are obtained. The fuzzy best dominants are given for the considered fuzzy differential subordinations in theorems which generate interesting corollaries when specific functions with remarkable geometric properties are used as fuzzy best dominants. An example is also shown in order to prove the applicability of the new results.
2. Main Results
The usage of the operator seen in Definition 8 defines a new fuzzy subclass of analytic functions as follows:
Definition 9. The class is composed of all functions with the propertywhere , , . We begin studying this subclass of functions:
Theorem 1. is a convex set.
Proof. Taking the functions
belonging to the class
, we have to prove that the function
belongs to the class
with
,
We have , , and
.
and we can write
Having we get and , .
In these conditions and we get , equivalently with and is a convex set. □
We give fuzzy differential subordinations obtained for the operator .
Theorem 2. Considering a convex function g in U and defining with when and , thenimplies the sharp result Proof. Differentiating relation
considering
z as variable, we get
and
and differentiating it again with respect to
z, we obtain
and the inequality (
2) representing the fuzzy differential subordination can be written
Denoted
where
we obtain
Applying Lemma 3, we get
and
g is the best dominant. □
We give an inclusion result for the class :
Theorem 3. Taking and , , with , , , thenwhere Proof. Making the same steps such as in the proof of Theorem 2, taking account the hypothesis of Theorem 3 and that
is a convex function, we obtain
with
Applying Lemma 2, we get
where
Since the function
g is convex and
is symmetric with respect to the real axis, we can write
and
, that give the inclusion (
3). □
Theorem 4. Taking a convex function g with the property define When , and the fuzzy differential subordination holdsthen we get the sharp result Proof. Considering we can write , and differentiating it we get
The inequality (
5) can be written as following
and applying Lemma 3, we get the sharp result
□
Example 1. Considera convex function in U and we obtain that , . Define Take , , , , and after a short computation we obtainandand differentiating it Applying Theorem 4 we get the following fuzzy differential subordinationinduce the following fuzzy differential subordination Theorem 5. Taking a holomorphic function h, such that and when , and the fuzzy differential subordination holdsthenwhere the fuzzy best dominant is convex. Proof. Considering
and using Lemma 1, we deduce that
is a convex function and it is a solution of the differential equation defining the fuzzy differential subordination (
6)
, therefore it is the fuzzy best dominant.
Differentiating
, we get
and (
6) can be written
□
Corollary 1. Taking the convex function in with , when and the fuzzy differential subordination holdsthenwhere the fuzzy best dominant is convex. Proof. Taking we obtain and , therefore
Following the same steps like in the proof of Theorem 5 with
, the fuzzy differential subordination (
7) can be written
Applying Lemma 2 for
and
, we obtain
where
□
Example 2. Considerand we obtain that , and . Taking account thath is a convex function in U. Taking , , , , as in Example 1, we haveandand differentiating it Applying Theorem 5 we get the following fuzzy differential subordinationinduce the following fuzzy differential subordination Theorem 6. Taking a convex function g with the property and defining , , when , and the fuzzy differential subordinationholds, then we obtain the sharp result Proof. Considering
and differentiating it we get
. With this notation, inequality (
8) can be written as
□
Example 3. Considerandas given in Example 1. Taking , , , , as in Example 1, we getandand applying Riemann–Liouville fractional integral of order λ we have Applying Theorem 6 we get the following fuzzy differential subordinationinduce the following fuzzy differential subordination Theorem 7. Taking a convex function g with the property and defining , when and the fuzzy differential subordinationholds, then we obtain the sharp result Proof. Considering
and differentiating it we obtain
and
Inequality (
9) can be written
Applying Lemma 3 for
and
, we get
□
Example 4. Considerandas given in Example 1. Taking , , , , as in Example 1, we obtainandand differentiating it Applying Theorem 7 we get the following fuzzy differential subordinationinduce the following fuzzy differential subordination Theorem 8. Considering a holomorphic function h, such that and when , and the fuzzy differential subordinationholds, thenwhere the fuzzy best dominant is convex. Proof. Considering
after differentiating it and making an easy computation, we get
and inequality (
10) can be written
Applying Lemma 2, we obtain
Taking into account that
applying Lemma 1 we obtain that
is a convex function and it is a solution of the differential equation of the fuzzy differential subordination (
10)
, thus it is the fuzzy best dominant. □
Example 5. Consideringas in Example 2, a convex function which satisfy conditions from Theorem 8, and taking , , , , we obtainandand differentiating it Applying Theorem 8 we get the following fuzzy differential subordinationinduce the following fuzzy differential subordination Theorem 9. Considering a convex function g with the property and defining , , , when and the fuzzy differential subordinationholds, then we obtain the sharp result Proof. Differentiating we obtain
Using this notation, the fuzzy differential subordination can be written
and applying Lemma 3, we obtain the sharp result
□
3. Conclusions
Applying the theory of fuzzy differential subordination, we studied a subclass of analytic function newly introduced regarding the operator . Several interesting properties are obtained for the defining subclass . New fuzzy differential subordinations are obtained for . To show how the results would be applied it is give an example. The operator introduced in Definition 8 and the subclass introduced in Definition 9 can be objects in other future studies. Other subclasses of analytic functions can be introduced regarding this operator and some properties for these subclasses can be investigated regarding coefficient estimates, closure theorems, distortion theorems, neighborhoods, and the radii of starlikeness, convexity, or close-to-convexity.
The dual theory of fuzzy differential superordination introduced in [
21] could be used for obtaining similar results involving the operator
and the class
which could be combined with the results presented here for sandwich-type theorems, as seen in [
17].