Abstract
At the present time, the study of various classical properties of the geometric function theory using the concept of a fuzzy subset remains limited. In this article, our main aim is to introduce the subclasses of spiral-like functions of complex order in terms of the fuzzy notion and we generalize these subclasses by applying a family of linear operators. The relationships between the newly defined subclasses are examined. In addition, we show that these subclasses are preserved under the well-known Bernardi integral operator.
1. Introduction
Let denote the class of analytic functions in the open unit disk . The class contains the functions , having the series of the form
For , we have , a class of normalized analytic functions in . We know that S, and C denote the subclasses of A of univalent functions, starlike functions and convex functions, respectively. The class of Caratheodory functions is denoted by P. Let . Then, denotes the subordination of functions and g and is defined as , where is the Schwartz function in (see [1]). In [2,3], the authors introduced and studied the concept of differential subordination. Fuzzy subordination and fuzzy differential subordination was first studied by G.I. Oros and Gh. Oros, see [4,5]. Several authors have contributed in the study of fuzzy differential subordination; for example, see [6,7,8,9,10]. Here, we give an overview of some useful basic concepts related to fuzzy differential subordination.
Definition 1
([11]). Let Y be a nonempty set. If F is mapping from Y to , then F is called a fuzzy subset on Y.
Alternatively, a fuzzy subset is also defined as the following:
Definition 2
([11]). A pair is called a fuzzy subset on Y, where is the membership function of the fuzzy set , and is the support of the fuzzy set .
Definition 3
([11]). Two fuzzy subsets, and of Y, are equal if and only if , whereas if and only if , .
Definition 4
([5]). Let and be a fixed point in D. Then, the analytic function is subordinate to the analytic function g (written as (or )) if;
Remark 1.
We can assume a function such as , as any of the following.
Remark 2.
If , as in Definition 4, then fuzzy subordination coincides with classical subordination.
The study of linear operators plays a significant role in this field of study. Various well-known operators are defined by using the convolution technique. In [12], the authors introduced the operators as follows:
Let and be defined as
Then,
where * denotes the convolution or Hadamard product.
This operator is known as the Noor integral operator of the order m. We note that and .
For any real , Cho and Kim [13] defined the multiplier transformation of functions by
where with .
Now, by making use of and , we introduce the operator as the following.
We use – to obtain the following identities.
The study of operators is an important topic in geometric function theory. After the concept was introduced by an author in [14], many well-known scholars [15,16,17,18] investigated this topic using the fuzzy subordination associated with certain operators. We mention a few recent contributions that were published with similar research directions [18,19,20,21,22]. The operators associated with fuzzy differential subordination have applications in various fields of study, such as engineering, biological systems with memory, computer graphics, physics, electric networks, turbulence, etc. In the context of the biological system, Baleanu et al. [23] proposed a new study on the mathematical modeling of the human liver with the Caputo–Fabrizio fractional derivative. Furthermore, Srivastava et al. [24] examined the transmission dynamics of the dengue infection in terms of fractional calculus. The authors in [25] studied the Korteweg–de Vries equation by using a new integral transform where the fractional derivative was proposed in the Caputo sense. This equation was developed to represent a broad spectrum of physics behaviors in the evolution and association of nonlinear waves. One can see [6,18,26,27] for more applications.
Motivated by this series of research, we defined certain new subclasses , and by using fuzzy subordination.
Denoted by T, the class of analytic functions , which are univalent convex functions in with and in . For , , , with , and ,, we define
and
where .
It is noted that
In application of the operator given in , some new classes are defined, as follows:
Definition 5.
Let , , δ be a real, , and . Then,
and
It is clear that
where , ,c and .
Special cases:
- (i)
- If and , then , and .
- (ii)
- If , , and , then and reduce to and , respectively, as shown by Shah et al. [10].
The main investigations of this article consist of the inclusion properties of the classes defined in Definition 5 and applications of the Bernardi integral operator.
2. Main Results
We will use the following lemmas to prove our results.
Lemma 1
([7]). Let , with , and , where
is analytic in ℧, then
implies
Lemma 2
([8]). Let ε, , , and a convex function ϰ satisfy
If p is analytic in ℧ with and is analytic in ℧ with , then
implies
2.1. Inclusion Results
Theorem 1.
If , , where and , , and then
for
and
for
Proof.
First, we have to prove the relation .
Let . Then, for is analytic in ℧ with , we set
Using identity and , we find
This implies
The logarithmic differentiation and yields
As , from , we have
Assuming that
Then, Lemma 2 and implies that . Hence, .
One can easily prove the relation by using a similar technique, as used in the proof of relation , along with the identity . □
Theorem 2.
If , , where , , and then
for
and
for
Proof.
For the proof of , we assume that . Then, by , . This implies, by using Theorem 1, . Again, by , we find .
The relation can be proved by using the same arguments as before. □
Theorem 3.
If , , α,, where , , , and then
for
and
for
Proof.
First, we prove the relation , and let . Then, by definition, there exists , such that
We consider, for is analytic in ℧ with ,
We use identities and , and find
As , from Theorem 1, we have . Further, for is analytic in ℧ with , we set
Again, we use in the above equation to obtain
Putting and in , we find
This implies
As and
We have
Therefore, Lemma 1 and imply that . Hence, .
One can easily prove the relation by using a similar technique as the one used in the proof of relation , along with the identity . □
2.2. The Integral Preserving Property
Theorem 4.
If , , , where , , and , and let , then , where
for
Proof.
Let . Then, for where is analytic in where , we set
From , we can write
This implies
Equivalently,
From and , we have
We take the logarithmic differentiation of both sides, and find
We use along with . As and we assume that , by using Lemma 2, we obtain that
and this completes the proof. □
Remark 3.
One can easily prove the invariance of the class under the Bernardi integral operator, as given by , by using Theorem 4 together with .
Theorem 5.
Let , , α, with , , , and , then, if
It follows that , where is given by .
Proof.
Let . Then, for is analytic in with , we set
where
with .
We use in , and find
Assume that, for to be analytic in with ,
From and , we can write
We use , and with the fact that , to conclude
As , due to the conditions in the theorems and Lemma 1, we obtain our required result. □
3. Conclusions
In this article, we examined the applications of fuzzy differential subordination in geometric function theory of complex analysis. We used the convolution technique to define a new operator for analytic functions. The principle of fuzzy subordination was applied to define certain subclasses of univalent functions associated with the family of linear operators. The inclusion relationships between the subclasses of the univalent functions were studied in terms of fuzzy subordination. Moreover, we proved that the Bernardi integral operator preserves these newly defined subclasses. In addition, generalized fuzzy close-to-convex functions were studied. This work will give an advantage to scholars in this field in their generalizations of various linear or convolution operators in terms of fuzzy subordination. Furthermore, one can study the properties discussed in this work for the different fuzzy subclasses of analytic functions.
Author Contributions
Conceptualization, S.A.S. and A.C.; methodology, S.A.S. and L.-I.C.; validation, A.C., A.F.A. and S.A.S.; formal analysis, L.-I.C. and A.C.; investigation, S.A.S. and A.F.A.; writing—original draft preparation, S.A.S. and L.-I.C.; writing—review and editing, A.F.A., L.-I.C. and S.A.S.; supervision, S.A.S. and A.C. All authors have read and agreed to the published version of the manuscript.
Funding
The research was funded by University of Oradea, Romania.
Data Availability Statement
Not applicable.
Acknowledgments
The first author would like to express thanks to Prince Sattam bin Abdulaziz University for the support and provide research environment.
Conflicts of Interest
The authors declare no conflict of interest.
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