Next Article in Journal
A Crank–Nicolson Compact Difference Method for Time-Fractional Damped Plate Vibration Equations
Previous Article in Journal
Resolution of an Isolated Case of a Quadratic Hypergeometric 2F1 Transformation
Previous Article in Special Issue
An MDL-Based Wavelet Scattering Features Selection for Signal Classification
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Fuzzy Differential Subordination for Meromorphic Function

1
Department of Mathematics, College of Science and Arts, Al-Badaya, Qassim University, Buraidah 51911, Saudi Arabia
2
Department of Mathematics, Faculty of Science, Damietta University, New Damietta 34517, Egypt
3
Department of Mathematics, Abdul Wali Khan University Mardan, Mardan 23200, Pakistan
*
Author to whom correspondence should be addressed.
Axioms 2022, 11(10), 534; https://doi.org/10.3390/axioms11100534
Submission received: 6 September 2022 / Revised: 28 September 2022 / Accepted: 1 October 2022 / Published: 7 October 2022
(This article belongs to the Special Issue Mathematical and Computational Applications)

Abstract

:
This paper is related to notions adapted from fuzzy set theory to the field of complex analysis, namely fuzzy differential subordinations. This work aims to present new fuzzy differential subordinations for which the fuzzy best dominant and fuzzy best subordinate are given, respectively. The original theorems proved in the paper generate interesting corollaries for particular choices of functions acting as fuzzy best dominant. Here, in this article, fuzzy differential subordination results are obtained using a new integral operator introduced in this paper for meromorphic function, such that the newly-defined integral operator is starlike and convex, respectively.

1. Introduction and Definitions

The introduction of the fuzzy set concept by Zadeh, in the paper “Fuzzy Sets” [1] in 1965, did not suggest the extraordinary evolution of the concept that followed. Received with distrust at first, the concept is very popular nowadays, having been adapted to several research topics. Mathematicians were also interested in embedding the concept of fuzzy set in their research and it was indeed included in many mathematical approaches. The review paper included in the present special issue, devoted to the celebration of the 100th anniversary of Zadeh’s birth [2], shows how fuzzy set theory has evolved related to certain branches of science, and points out the contribution of one of Zadeh’s disciples, Professor Dzitac, to the development of soft computing methods connected with fuzzy set theory. Professor Dzitac has celebrated his friendship with the multidisciplinary scientist, Zadeh, by writing the introductory paper of a special issue on fuzzy logic dedicated to the centenary of Zadeh’s birth [3]. As far as complex analysis is concerned, fuzzy set theory has been included in studies related to geometric function theory in 2011, when the first paper appeared introducing the notion of subordination in fuzzy set theory [4] which has had its inspiration in the classical aspects of subordination introduced by Miller and Mocanu [5,6]. The next papers published followed the line of research set by Miller and Mocanu and referred to fuzzy differential subordination, adapting notions from the already well-established theory of differential subordination [7,8,9]. The idea was soon picked up by researchers in geometric function theory and all the classical lines of research on this topic was adapted to the new fuzzy aspects. A review paper, published in 2017 [10], included in its references the first published papers related to this topic, validating its development. The dual notion of fuzzy differential subordination was also introduced in 2017 [11]. An important topic in geometric function theory is conducting studies which involve operators. Such studies for obtaining new fuzzy subordination results were published shortly after the concept was introduced, in 2013 [12], and continued in the following years [13,14,15,16] and later adding super-ordination results [17,18,19]. During the last years, many papers were published which show that the research on this topic is in continuous development process and we mention only a few here [15,20,21,22,23].
Fuzzy differential subordination involving fractional calculus has had tremendous development in recent years proving to have applications in many research domains such as physics, engineering, turbulence, electric networks, biological systems with memory, computer graphics, etc. As an For example, the Korteweg–de Vries equation, developed to represent a broad spectrum of physics behaviors of the evolution and association of nonlinear waves, is studied using a new integral transform where the fractional derivative is proposed in the Caputo sense [24]. Related to biological systems, examples can be given as the new study on the mathematical modeling of the human liver with the Caputo–Fabrizio fractional derivative proposed in [25] and fractional calculus analysis of the transmission dynamics of the dengue infection seen in [26]. For more applications see [15,19,27,28].
Following this line of research, a new integral operator is introduced in this paper using a meromorphic function and having, as inspiration, the operator studied by Jung, Kim and Srivastava [29] in 1993, by taking specific values for parameters involved in its definition. Fuzzy differential subordinations are obtained, and the fuzzy best dominants are given, which facilitate obtaining sufficient conditions for the univalence of this operator.

2. Preliminaries

Let H U be the class of functions analytic in U = ζ ˙ : ζ ˙ C and ζ ˙ < 1 and H a , n be the subclass of H U consisting of functions of the form
H a , n = ϑ : ϑ H U and ϑ ζ ˙ = a + a n ζ ˙ n + a n + 1 ζ ˙ n + 1 + , ζ ˙ U .
with H = H 1 , 1 .
Let C and N denote the set of complex numbers and the set of all positive integers, respectively. For Ω C , we denote by H Ω the class of meromorphic function in Ω . For d N , we denote by M d the class of meromorphic function defined by
M d : = ϑ : ϑ H U and ϑ ζ ˙ = 1 ζ ˙ + n = d + 1 a n ζ ˙ n ζ ˙ U * = U 0 ; d N .
where U * is a punctured disc defined by
U * : = ζ ˙ : ζ ˙ C and 0 < ζ ˙ < 1 .
In particular, we write M : = M 1 .
And we denote by MS * and MC the classes of M , which are respectively, meromorphic starlike and meromorphic convex in U * , so that, by definition, we have
MS * : = ϑ : ϑ M and Re ζ ˙ ϑ ζ ˙ ϑ ζ ˙ > 0 ζ ˙ U * ,
and
MC : = ϑ : ϑ M and Re 1 + ζ ˙ ϑ ζ ˙ ϑ ζ ˙ > 0 ζ ˙ U * .
Definition 1
([30,31]). Let ϑ 1 and ϑ 2 be members of H U . The function ϑ 1 is said to be subordinate to ϑ 2 , or ϑ 2 is said to be superordinate to ϑ 1 , if there exist a function w analytic in U with w 0 = 0 and | w ( ζ ˙ ) | < 1   ( ζ ˙ U ) , such that ϑ 1 ( ζ ˙ ) = ϑ 2 ( w ( ζ ˙ ) ) . In such case we write ϑ 1 ( ζ ˙ ) ϑ 2 ( ζ ˙ ) . If ϑ 2 is univalent, then ϑ 1 ϑ 2 , if and only if ϑ 1 ( 0 ) = ϑ 2 ( 0 ) and ϑ 1 U ϑ 2 U .
To introduce the notion of fuzzy differential subordination, we use the following definitions and propositions:
Definition 2
([32]). Assume that Y be a non-empty set. An application F : Y [ 0 , 1 ] is called fuzzy subset. A pair B , F B , where F B : Y [ 0 , 1 ] and
B = x Y : 0 < F B x 1 = sup B , F B
is called a fuzzy set. The function F B is called membership function of the fuzzy set B , F B .
Definition 3
([13]). Let F : C R + be a function such that
F C ( ζ ˙ ) = | F ( ζ ˙ ) | ( ζ ˙ C ) .
Denote by
F C C = { ζ ˙ : ζ ˙ C and 0 < | F ( ζ ˙ ) | 1 } : = S u p p ( C , F C ( ζ ˙ ) ) ,
the fuzzy subset of the set C of complex numbers. We call the following subset:
F C ( C ) = { ζ ˙ : ζ ˙ C and 0 < | F ( ζ ˙ ) | 1 } : = U F ( 0 , 1 ) ,
the fuzzy unit disk. It is observed that ( C , F C ( ζ ˙ ) ) is the same as its fuzzy unit disk U F 0 , 1 .
Proposition 1
([4]). (i)    If B , F B = U , F U , then we have B = U , where B = sup B , F B and U = sup U , F U .
(ii) 
If B , F B U , F U , then we have B U , where B = sup B , F B and U = sup U , F U .
Let ϑ , g H U . We denote
ϑ U = ϑ ζ ˙ : 0 < F ϑ U ϑ ζ ˙ 1 , ζ ˙ U = sup ϑ U , F ϑ U
and
g U = g ζ ˙ : 0 < F g U g ζ ˙ 1 , ζ ˙ U = sup g U , F g U .
Definition 4
([4]). Let ζ ˙ 0 U and ϑ , g H U . The function ϑ is said to be fuzzy subordinate to g , written as ϑ F g or ϑ ( ζ ˙ ) F g ( ζ ˙ ) , when the following conditions are satisfied:
i ϑ ζ ˙ 0 = g ζ ˙ 0 i i F ϑ U ϑ ζ ˙ F g U g ζ ˙ , ζ ˙ U .
Proposition 2
([4]). Assume that ζ ˙ 0 U and ϑ , g H U . If ϑ ( ζ ˙ ) F g ( ζ ˙ ) , ζ ˙ U , then
i ϑ ζ ˙ 0 = g ζ ˙ 0 i i ϑ U g U and F ϑ U ϑ ζ ˙ F g U g ζ ˙ , ζ ˙ U ,
where ϑ U and g U are defined by (4) and (5), respectively.
Definition  5
([7]). Assume that Φ : C 3 × U C and H be an analytic function with Φ a , 0 , 0 , 0 = H 0 = a . If p is analytic in U with p 0 = a and satisfies the second-order fuzzy differential subordination
F Φ C 3 × U Φ p ζ ˙ , ζ ˙ p ζ ˙ , ζ ˙ 2 p ζ ˙ ; ζ ˙ F H U H ζ ˙ ,
i.e.,
Φ p ( ζ ˙ ) , ζ ˙ p ( ζ ˙ ) , ζ ˙ 2 p ( ζ ˙ ) ; ζ ˙ ϑ H ( ζ ˙ ) .
then p is called a fuzzy solution of the fuzzy differential subordination. The univalent function q is called a fuzzy dominant of the fuzzy solutions for the fuzzy differential subordination if
F p U p ( ζ ˙ ) F q U q ( ζ ˙ ) , i . e . , p ( ζ ˙ ) ϑ q ( ζ ˙ ) , ζ ˙ U .
for all p satisfying (6). A fuzzy dominant q ˜ that satisfies
F q ˜ U q ˜ ( ζ ˙ ) F q U q ( ζ ˙ ) , i . e . , q ˜ ( ζ ˙ ) ϑ q ( ζ ˙ ) , ζ ˙ U .
for all fuzzy dominant q of (6) is said to be the fuzzy best dominant of (6).
The set of all analytic and injective functions q ( ζ ˙ ) denoted by Q on U ˜ E q , where
E q = ζ U : lim ζ ˙ ζ q ( ζ ˙ ) = ,
and are such that q ζ 0 for ζ U E q . Further let the subclass of Q for which q 0 = a be denoted by Q a with Q 1 Q 1 .
The research presented in this paper is done in the general environment known in the theory of differential subordination combined with fuzzy set notions introduced in [4,5,6,7].
In our investigation, we need the following lemmas which are proved by Miller and Mocanu [30,31].
Lemma 1
([30]). Let Ψ Ψ n Ω , q with q 0 = a . If the analytic function g ( ζ ˙ ) = a + a n ζ ˙ n + a n + 1 ζ ˙ n + 1 + , satisfies
Ψ g ( ζ ˙ ) , ζ ˙ g ( ζ ˙ ) , ζ ˙ 2 g ( ζ ˙ ) ; ζ ˙ Ω
then g ( ζ ˙ ) q ( ζ ˙ ) .
Lemma 2
([31]). Let Ψ Ψ n Ω , q with q 0 = a . If g ( ζ ˙ ) Q ( ζ ˙ ) and
Ψ g ( ζ ˙ ) , ζ ˙ g ( ζ ˙ ) , ζ ˙ 2 g ( ζ ˙ ) ; ζ ˙
is univalent in U then
Ω Ψ g ( ζ ˙ ) , ζ ˙ g ( ζ ˙ ) , ζ ˙ 2 g ( ζ ˙ ) ; ζ ˙ : ζ ˙ U ,
implies g ( ζ ˙ ) q ( ζ ˙ ) .
Various families of linear or convolution operators are known to play important roles in the Geometric Function Theory of Complex Analysis and its related fields. One can indeed express derivative and integral operators as convolutions of some families of meromorphic functions. This kind of formalism makes further mathematical investigation much easier and also aids in a better understanding of the geometric properties of the operators involved.
Analogous to the operators defined by Jung, Kim, and Srivastava [29] on the normalized analytic functions, we now define the following integral operators P β α : M M
P β α = β α Γ α 1 ζ ˙ β + 1 0 ζ ˙ ln ζ ˙ t α 1 t β ϑ t d t α > 0 , β > 0 ; ζ ˙ U *
and
J β α = β ζ ˙ β + 1 0 ζ ˙ t β ϑ t d t β > 0 ; ζ ˙ U
where Γ α is the familiar Gamma function. Moreover, by making use of the Hadamard product (or convolution), for
ϑ ζ ˙ = 1 ζ ˙ + n = 1 a n ζ ˙ n ζ ˙ U * = U 0 ,
we define
P β α ϑ ζ ˙ : = P β α ζ ˙ ϑ ζ ˙ = 1 ζ ˙ + n = 1 β n + β + 1 α a n ζ ˙ n α > 0 , β > 0 .
and
J β α ϑ ζ ˙ : = J β α ζ ˙ ϑ ζ ˙ = 1 ζ ˙ + n = 1 β n + β + 1 a n ζ ˙ n β > 0 ,
By virtue of (9) and (10), we see that
J β α ϑ ζ ˙ = P β 1 ϑ ζ ˙ ,
ζ ˙ P β α ϑ ζ ˙ = β P β α 1 ϑ ζ ˙ β + 1 P β α ϑ ζ ˙ α > 0 , β > 0
We need the following Lemma to investigate our main results.
Lemma 3
([30]). Let H M and suppose that
K ζ ˙ = 1 ζ ˙ 0 ζ ˙ H t d t ζ ˙ U * .
If
R e 1 + ζ ˙ H ζ ˙ H ζ ˙ > 1 2 ζ ˙ U * ,
then K C .
Lemma 4
([33]). Suppose that the convex function H satisfies H 0 = a , let μ C * = C 0 such that Re μ 0 . If P H a , n with P 0 = a and Ψ : C 2 × U C , Ψ P ζ ˙ + ζ ˙ P ζ ˙ = P ζ ˙ + 1 μ ζ ˙ P ζ ˙ is holomorphic in U , then
F Ψ C 2 × U P ζ ˙ + 1 μ ζ ˙ P ζ ˙ F H U H ζ ˙ P ζ ˙ + 1 μ ζ ˙ P ζ ˙ ϑ H ζ ˙ ζ ˙ U ,
implies
F P U P ζ ˙ F q U q ζ ˙ F H U H ζ ˙ .
i.e.,
P ζ ˙ ϑ q ζ ˙ ,
where
q ζ ˙ = μ n ζ ˙ μ / n 0 ζ ˙ t μ n 1 H t d t ,
is convex and best dominant.
Lemma 5
([33]). Suppose that q is a convex function in U , let H ζ ˙ = q ζ ˙ + n v ζ ˙ q ζ ˙ , v > 0 and n N . If P H q 0 , n and Ψ : C 2 × U C , Ψ P ζ ˙ + ζ ˙ P ζ ˙ = P ζ ˙ + v ζ ˙ P ζ ˙ is holomorphic in U , then
F P U P ζ ˙ + ζ ˙ P ζ ˙ F H U H ζ ˙ P ζ ˙ + v ζ ˙ P ζ ˙ ϑ q ζ ˙ ,
then
F P U P ζ ˙ F q U q ζ ˙ , ζ ˙ U
i.e.,
P ζ ˙ ϑ q ζ ˙ .
and q is the best fuzzy dominant.
Recently, Srivastava [15], Lupaş [27,33], Oros [21,22,34], and Wanas [35,36] have obtained fuzzy differential subordination results for certain classes of holomorphic functions.

3. Main Results

Theorem 1.
Suppose the convex function K in U * , satisfies K 0 = 1 .
H = K ζ ˙ + ζ ˙ K ζ ˙ ζ ˙ U *
Let ϑ M , and us satisfy the following fuzzy differential subordination:
F Ψ C 2 × U * β P β α 1 ϑ ζ ˙ β + 1 P β α ϑ ζ ˙ + ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ,
implies
β P β α 1 ϑ ζ ˙ β + 1 P β α ϑ ζ ˙ + ζ ˙ ζ ˙ P β α ϑ ζ ˙ ϑ H ζ ˙
then
F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ζ ˙ P β α ϑ ζ ˙ ϑ K ζ ˙ .
This result is sharp.
Proof. 
Let us assume
P ζ ˙ = ζ ˙ P β α ϑ ζ ˙ .
Therefore in the view of (11) and (13), we have
P ζ ˙ + ζ ˙ P ζ ˙ = β 1 ζ ˙ + n = 1 β n + β + 1 α 1 a n ζ ˙ n β + 1 1 ζ ˙ + n = 1 β n + β + 1 α a n ζ ˙ n + 1 ζ ˙ + n = 1 n 2 β n + β + 1 α a n ζ ˙ n = β P β α 1 ϑ ζ ˙ β + 1 P β α ϑ ζ ˙ + ζ ˙ ζ ˙ P β α ϑ ζ ˙ .
According to (12) and (14), we deduce that
F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ,
implies
F Ψ C 2 × U * P ζ ˙ + ζ ˙ P ζ ˙ F H U * H ζ ˙ F K U * K ζ ˙ + ζ ˙ K ζ ˙ .
Thus by applying Lemma 4 with μ = 1 , we obtain
F P U * P ζ ˙ F K U K ζ ˙ F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F K U * K ζ ˙
i.e.,
ζ ˙ P β α ϑ ζ ˙ ϑ K ζ ˙ ,
It has sharp and equal boundaries for the Möbius function, ϑ 0 ζ ˙ = 1 + ζ ˙ 1 ζ ˙ or any other suitable one. The proof is complete. □
Theorem 2.
Suppose the convex function K in U * , satisfies K 0 = 1 .
H = K ζ ˙ + ζ ˙ K ζ ˙ ζ ˙ U *
Let ϑ M and us satisfy the following fuzzy differential subordination:
F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ζ ˙ P β α ϑ ζ ˙ ϑ H ζ ˙
then
F P β α ϑ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ P β α ϑ ζ ˙ ϑ K ζ ˙ .
The result is sharp, that is, the assertion holds true for a suitably specified function.
Proof. 
Let us assume
P ζ ˙ = P β α ϑ ζ ˙
Therefore in the view of (11) and (16), we have
P ζ ˙ + ζ ˙ P ζ ˙ = 1 ζ ˙ + n = 1 β n + β + 1 α a n ζ ˙ n + 1 ζ ˙ + n = 1 n β n + β + 1 α a n ζ ˙ n = n = 1 n + 1 β n + β + 1 α a n ζ ˙ n .
We find that
P ζ ˙ + ζ ˙ P ζ ˙ = ζ ˙ P β α ϑ ζ ˙ .
We, thus, see the following inequality:
F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ,
implies that
F Ψ C 2 × U * P ζ ˙ + ζ ˙ P ζ ˙ F H U * H ζ ˙ F K U * K ζ ˙ + ζ ˙ K ζ ˙ .
Thus by applying Lemma 5, we obtain
F P U * P ζ ˙ F K U * K ζ ˙ F P β α ϑ ζ ˙ P β α ϑ ζ ˙ F K U * K ζ ˙ ,
which implies that
P β α ϑ ζ ˙ ϑ K ζ ˙ .
The result is easily seen to be sharp, that is, the result holds true for a suitably specified function. The proof of Theorem 2 is, thus, completed. □
Theorem 3.
Let H H U * with H 0 = 1 , such that
R e 1 + ζ ˙ H ζ ˙ H ζ ˙ > 1 2 ζ ˙ U *
If ϑ M and the following fuzzy differential subordination holds true:
F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ζ ˙ P β α ϑ ζ ˙ ϑ H ζ ˙
then
F P β α ϑ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ P β α ϑ ζ ˙ ϑ K ζ ˙ .
where the function K ζ ˙ , given by
K ζ ˙ = 1 ζ ˙ 0 ζ ˙ H t d t
is convex and is the fuzzy best dominant.
Proof. 
Assume that
P ζ ˙ = P β α ϑ ζ ˙ .
It is clear that P ζ ˙ H 1 , 1 . Suppose that H H U * with H 0 = 1 , such that
Re 1 + ζ ˙ H ζ ˙ H ζ ˙ > 1 2 ζ ˙ U *
From Lemma 3, we have
K ζ ˙ = 1 ζ ˙ 0 ζ ˙ H t d t
which is convex and satisfies the fuzzy differential subordination (18) . Since
H ζ ˙ = K ζ ˙ + ζ ˙ K ζ ˙ ζ ˙ U *
It is the fuzzy best dominant.
We next observe that
P ζ ˙ + ζ ˙ P ζ ˙ = n = 1 n + 1 β n + β + 1 α a n ζ ˙ n = ζ ˙ P β α ϑ ζ ˙ .
In the view of (20), the fuzzy differential subordination (18) becomes
F P U P ζ ˙ + ζ ˙ P ζ ˙ F H U H ζ ˙ .
Thus by applying Lemma 5 with v = 1 , we obtain
F P U * P ζ ˙ F K U * K ζ ˙ .
This completes the proof. □
Upon setting
H ζ ˙ = 1 + 2 β 1 ζ ˙ 1 + ζ ˙ ζ ˙ U *
in Theorem 3, we can deduce the following corollary.
Corollary 1.
Let
H ζ ˙ = 1 + 2 β 1 ζ ˙ 1 + ζ ˙ ζ ˙ U *
be normalized convex function in U * with H 0 = 1 and 0 β < 1 . If the function ϑ M satisfies the following fuzzy differential subordination:
F ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ζ ˙ P β α ϑ ζ ˙ ϑ H ζ ˙ ,
then the function K ζ ˙ is given by
K ζ ˙ = 2 β 1 + 2 1 β ζ ˙ log 1 + ζ ˙ ,
is convex and is the fuzzy best dominant.
Theorem 4.
Suppose K is convex function in U * . Such that K 0 = 1 ,
H ζ ˙ = K ζ ˙ + ζ ˙ K ζ ˙ .
Let ϑ M , and ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ is holomorphic in U * . If
F ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ ϑ H ζ ˙ ,
then
F P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ,
i.e.,
P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ ϑ K ζ ˙ .
This result is sharp.
Proof. 
Assume that
P ζ ˙ = P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ .
Therefore we note that P ζ ˙ H 1 , 1 .
Differentiating both sides of (23) with respect to ζ ˙ , it yields
P ζ ˙ = P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ P ζ ˙ P β α ϑ ζ ˙ P β α ϑ ζ ˙ .
Then
P ζ ˙ + ζ ˙ P ζ ˙ = P β α ϑ ζ ˙ ζ ˙ P β α 1 ϑ ζ ˙ + P β α ϑ ζ ˙ ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ P β α ϑ ζ ˙ 2 = ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ .
Utilizing (24) in (22), we can get
F ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ F H U * H ζ ˙ ,
implies
F P U P ζ ˙ + ζ ˙ P ζ ˙ F H U * H ζ ˙ F K U * K ζ ˙ + ζ ˙ K ζ ˙ .
Thus by applying Lemma 5 with v = 1 , we obtain
F P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ F K U * K ζ ˙ ,
i.e.,
P β α 1 ϑ ζ ˙ P β α ϑ ζ ˙ ϑ K ζ ˙ .
It has sharpness consider Möbius function, ϑ 0 ζ ˙ = 1 + ζ ˙ 1 ζ ˙ or any other suitable one. The proof of Theorem 4 is complete. □

4. Conclusions

In our present investigation of applications of fuzzy differential subordination in Geometric Function Theory of Complex Analysis, we successfully made use of integral operator P β α ϑ ζ ˙ for meromorphic function. Another avenue for further research on this subject is provided by the fact that, in the theory of differential subordinations and differential super-ordinations, there are differential subordinations and differential subordinations of the third and higher orders as well (see, for details, [30]; see also [37] or recent developments on this subject). In this presentation, we only used and explored the second-order differential subordinations and differential super-ordinations. This differential subordination is very helpful in computer graphics, etc.

Author Contributions

Conceptualization, S.E.-D., M.A., A.A. and N.K. 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.

Acknowledgments

The researchers would like to thank the Deanship of Scientific Research, Qassim University, for funding the publication of this project.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Zadeh, L.A. Fuzzy sets. Inf. Control 1965, 8, 338–353. [Google Scholar] [CrossRef] [Green Version]
  2. Dzitac, S.; Nădăban, S. Soft computing for decision-making in fuzzy environments: A tribute to Professor Ioan Dzitac. Mathematics 2021, 9, 1701. [Google Scholar] [CrossRef]
  3. Dzitac, I. Zadeh’s Centenary. Int. J. Comput. Commun. Control 2021, 16, 4102. [Google Scholar] [CrossRef]
  4. Oros, G.I.; Oros, G. The notion of subordination in fuzzy sets theory. Gen. Math. 2011, 19, 97–103. [Google Scholar]
  5. Miller, S.S.; Mocanu, P.T. Second order differential inequalities in the complex plane. J. Math. Anal. Appl. 1978, 65, 289–305. [Google Scholar] [CrossRef] [Green Version]
  6. Miller, S.S.; Mocanu, P.T. Differential subordinations and univalent functions. Mich. Math. J. 1981, 28, 157–172. [Google Scholar] [CrossRef]
  7. Oros, G.I.; Oros, G. Fuzzy differential subordination. Acta Univ. Apulensis 2012, 30, 55–64. [Google Scholar]
  8. Oros, G.I.; Oros, G. Dominants and best dominants in fuzzy differential subordinations. Stud. Univ. Babes-Bolyai Math. 2012, 57, 239–248. [Google Scholar]
  9. Oros, G.I.; Oros, G. Briot-Bouquet fuzzy differential subordination. An. Univ. Oradea Fasc. Mat. 2012, 19, 83–87. [Google Scholar]
  10. Dzitac, I.; Filip, F.G.; Manolescu, M.J. Fuzzy logic is not fuzzy: World-renowned computer scientist Lotfi A. Zadeh. Int. J. Comput. Commun. Control 2017, 12, 748–789. [Google Scholar] [CrossRef] [Green Version]
  11. Atshan, W.G.; Hussain, K.O. Fuzzy differential superordination. Theory Appl. Math. Comput. Sci. 2017, 7, 27–38. [Google Scholar]
  12. Alb Lupaş, A. A note on special fuzzy differential subordinations using generalized Salagean operator and Ruscheweyh derivative. J. Comput. Anal. Appl. 2013, 15, 1476–1483. [Google Scholar]
  13. Alb Lupaş, A.; Oros, G. On special fuzzy differential subordinations using Sălăgean and Ruscheweyh operators. Appl. Math. Comput. 2015, 261, 119–127. [Google Scholar]
  14. Venter, A.O. On special fuzzy differential subordination using Ruscheweyh operator. An. Univ. Oradea Fasc. Mat. 2015, 22, 167–176. [Google Scholar]
  15. Srivastava, H.M.; El-Deeb, S.M. Fuzzy differential subordinations based upon the Mittag-Leffler type Borel distribution. Symmetry 2021, 13, 1023. [Google Scholar] [CrossRef]
  16. Wanas, A.K.; Majeed, A.H. Fuzzy differential subordination properties of analytic functions involving generalized differential operator. Sci. Int. 2018, 30, 297–302. [Google Scholar]
  17. Ibrahim, R.W. On the subordination and super-ordination concepts with applications. J. Comput. Theor. 2017, 14, 2248–2254. [Google Scholar] [CrossRef]
  18. Altai, N.H.; Abdulkadhim, M.M.; Imran, Q.H. On first order fuzzy differential superordination. J. Sci. Arts 2017, 3, 407–412. [Google Scholar]
  19. Alb Lupaş, A. Applications of the fractional calculus in fuzzy differential subordinations and superordinations. Mathematics 2021, 9, 2601. [Google Scholar] [CrossRef]
  20. El-Deeb, S.M.; Alb Lupaş, A. Fuzzy differential subordinations associated with an integral operator. An. Univ. Oradea Fasc. Mat. 2020, 27, 133–140. [Google Scholar]
  21. Alb Lupaş, A.; Oros, G.I. New applications of Salagean and Ruscheweyh operators for obtaining fuzzy differential subordinations. Mathematics 2021, 9, 2000. [Google Scholar] [CrossRef]
  22. El-Deeb, S.M.; Oros, G.I. Fuzzy differential subordinations connected with the linear operator. Math. Bohem. 2021, 146, 397–406. [Google Scholar] [CrossRef]
  23. Oros, G.I. New fuzzy differential subordinations. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2021, 70, 229–240. [Google Scholar] [CrossRef]
  24. Rashid, S.; Khalid, A.; Sultana, S.; Hammouch, Z.; Shah, R.; Alsharif, A.M. A novel analytical view of time-fractional Korteweg-De Vries equations via a new integral transform. Symmetry 2021, 13, 1254. [Google Scholar] [CrossRef]
  25. Baleanu, D.; Jajarmi, A.; Mohammadi, H.; Rezapour, S. A new study on the mathematical modelling of human liver with Caputo–Fabrizio fractional derivative. Chaos Solitons Fractals 2020, 134, 109705. [Google Scholar] [CrossRef]
  26. Srivastava, H.M.; Jan, R.; Jan, A.; Deebani, W.; Shutaywi, M. Fractional-calculus analysis of the transmission dynamics of the dengue infection. Chaos Interdiscip. J. Nonlinear Sci. 2021, 31, 053130. [Google Scholar] [CrossRef]
  27. Alb Lupaş, A.; Cătaş, A. Fuzzy differential subordination of the Atangana–Baleanu fractional integral. Symmetry 2021, 13, 1929. [Google Scholar] [CrossRef]
  28. Oros, G.I.; Dzitac, S. Applications of subordination chains and fractional integral in fuzzy differential subordinations. Mathematics 2022, 10, 1690. [Google Scholar] [CrossRef]
  29. Jung, I.B.; Kim, Y.C.; Srivastava, H.M. The Hardy space of analytic functions associated with certain one-parameter families of integral operators. J. Math. Anal. Appl. 1993, 176, 138–147. [Google Scholar] [CrossRef] [Green Version]
  30. Miller, S.S.; Mocanu, P.T. Differential Subordinations: Theory and Applications; CRC Press: Boca Raton, FL, USA, 2000. [Google Scholar]
  31. Miller, S.S.; Mocanu, P.T. Subordinants of differential superordinations. Complex Var. 2003, 48, 815–826. [Google Scholar] [CrossRef]
  32. Gal, S.G.; Ban, A.I. Elemente de Matematica Fuzzy; University of Oradea: Oradea, Romania, 1996. [Google Scholar]
  33. Alb Lupaş, A. A note on special fuzzy differential subordinations using multiplier transformation and Ruscheweyh derivative. J. Comput. Anal. Appl. 2018, 25, 1116–1124. [Google Scholar]
  34. Oros, G.I. Fuzzy differential subordinations obtained using a hypergeometric integral operator. Mathematics 2021, 9, 2539. [Google Scholar] [CrossRef]
  35. Altınkaya, Ş.; Wanas, A.K. Some properties for fuzzy differential subordination defined by Wanas operator. Earthline J. Math. Sci. 2020, 4, 51–62. [Google Scholar] [CrossRef]
  36. Wanas, A.K.; Bulut, S. Some results for fractional derivative associated with fuzzy differential subordinations. J. Al-Qadisiyah Comput. Sci. Math. 2020, 12, 27. [Google Scholar]
  37. Bulboaca, T. Differential Subordinations and Superordinations: New Results; House of Scientific Boook Publ.: Cluj-Napoca, Romania, 2005. [Google Scholar]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

El-Deeb, S.; Khan, N.; Arif, M.; Alburaikan, A. Fuzzy Differential Subordination for Meromorphic Function. Axioms 2022, 11, 534. https://doi.org/10.3390/axioms11100534

AMA Style

El-Deeb S, Khan N, Arif M, Alburaikan A. Fuzzy Differential Subordination for Meromorphic Function. Axioms. 2022; 11(10):534. https://doi.org/10.3390/axioms11100534

Chicago/Turabian Style

El-Deeb, Sheza, Neelam Khan, Muhammad Arif, and Alhanouf Alburaikan. 2022. "Fuzzy Differential Subordination for Meromorphic Function" Axioms 11, no. 10: 534. https://doi.org/10.3390/axioms11100534

APA Style

El-Deeb, S., Khan, N., Arif, M., & Alburaikan, A. (2022). Fuzzy Differential Subordination for Meromorphic Function. Axioms, 11(10), 534. https://doi.org/10.3390/axioms11100534

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop