Abstract
Based upon the Pascal distribution series , we can obtain a set of fuzzy differential subordinations in this investigation. We also newly obtain class of univalent analytic functions defined by the operator , give certain properties for the class and also obtain some applications connected with a special case for the operator. New research directions can be taken on fuzzy differential subordinations associated with symmetry operators.
MSC:
30C45; 30C50; 30C80
1. Introduction
Let represent the class of holomorphic and univalent functions on such that and let denote the class of holomorphic functions on . The class of holomorphic functions in the open unit disk of the complex plane is denoted in this study by a note , with standing as the unit disk’s boundary. For , we define
and
We denote by
which is the set of convex functions on .
Let and be analytic in Then is subordinate to written as if there exists a Schwarz function which is analytic in with and for all such that Furthermore, if the function is univalent in then we have the following equivalence (see [1,2]):
In order to introduce the notion of fuzzy differential subordination, we use the following definitions and propositions:
Definition 1
([3]). Assume that is a Fuzzy subset and is an application. A pair of where and
a fuzzy subset. The fuzzy set is called a function .
Let be denoted by
and
Proposition 1
([4]). (i) If , then we have where and if , then we have where and
Definition 2
([4]). Let be a fixed point and let the functions The function Υ is said to be fuzzy subordinate to g, and we write or which satisfies the following conditions:
- (i)
- (ii)
Proposition 2
([4]). Assume that is a fixed point and the functions If then
- (i)
- (ii)
Definition 3
([5]). Assume that and , . If p satisfies the requirements of the second-order fuzzy differential subordination and is analytic in Λ, with ,
If q is a fuzzy dominant of the fuzzy differential subordination solutions, then p is said to be a fuzzy solution of the fuzzy differential subordination and satisfies
for each and every p satisfying (4).
Definition 4.
A fuzzy dominant that satisfies
then
The fuzzy best dominant of (4) is referred to for all fuzzy dominants.
Assume the function is given by
The Hadamard (or convolution) product of and is defined as
A variable x is said to have the Pascal distribution if it takes the values with the probabilities , , , , …, respectively, where q and r are called the parameters, and thus we have the probability formula
Now we present a power series whose coefficients are Pascal distribution probabilities, i.e.,
We easily determine from the ratio test that the radius of convergence of the above power series is at least ; hence, .
We define the functions
El-Deeb and Bulboacă [6] introduced the linear operator defined by
where is given by (1), and the symbol “*” stands for the Hadamard (or convolution) product.
Remark 1.
(i) For the operator reduces to , introduced and studied by El-Deeb et al. [7]; (ii) for and the operator reduces to , introduced and studied by El-Deeb et al. [7].
Using the operator , we create a class of analytical functions and derive several fuzzy differential subordinations for this class.
Definition 5.
If the function belongs to the class for all and satisfies the inequality
2. Preliminary
The following lemmas are needed to show our results.
Lemma 1
([2]). Assume that and . If , then .
Lemma 2
(Theorem 2.6 in [8]). If is a convex function such that , with If such that , is an analytic function in Λ and
then
where
The function q is convex, and it is the fuzzy best dominant.
Lemma 3
(Theorem 2.7 in [8]). Let be a convex function in Λ and where and if
and
Then
This result is sharp.
We define the fuzzy differential subordination general theory and its applications (see [9,10,11,12,13]). The method of fuzzy differential subordination is applied in the next section to obtain a set of fuzzy differential subordinations related to the operator .
3. Main Results
Assume that , and are mentioned throughout this paper.
Theorem 1.
Let k belong to in Λ, and If and
then
implies
Proof.
We denote
Using Lemma (3), we obtain
and therefore, where k is the fuzzy best dominant. □
Putting and in Theorem 1, we obtain the following example since the operator reduces to .
Example 1.
Theorem 2.
Proof.
A function h belongs to , and we obtain from the hypothesis of Theorem 2 using the same technique as that in the proof of Theorem 1 that
where is defined in (10). By using Lemma 2, we obtain
which implies
where
where is symmetric with respect to the real axis, so we have
and □
Theorem 3.
Assume that k belongs to in Λ, that and that When and the fuzzy differential subordination is satisfied,
holds, then
Proof.
Let
and we obtain that
so
implies
Using the Lemma 3, we obtain
and we obtain
□
Theorem 4.
Consider , which satisfies when . If the fuzzy differential subordination
then
where
the function k is convex, and it is the fuzzy best dominant.
Proof.
Let
where From Lemma 1, we have
belongs to the class which satisfies the fuzzy differential subordination (17). Since
it is the fuzzy best dominant. We have
then (17) becomes
By using Lemma 3, we obtain
then
□
Putting in Theorem 4. As a result, we have the following corollary:
Corollary 1.
Let be a convex function in Λ, with If and verifies the fuzzy differential subordination
then
then
where
the function k is convex and it is the fuzzy best dominant.
Putting and in Corollary 1, we obtain the following example.
Example 2.
Let be a convex function in Λ, with If and verifies the fuzzy differential subordination
then
where
4. Conclusions
All of the above results provide information about fuzzy differential subordinations for the operator ; we also provide certain properties for the class of univalent analytic functions. Using these classes and operators, we can create some simple applications.
Author Contributions
Conceptualization, S.M.E.-D. and L.-I.C.; Formal analysis, S.M.E.-D. and L.-I.C.; Investigation, S.M.E.-D. and L.-I.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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