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ABSTRACT
In this study, we establish a new class of Kantorovich-Stancu type Bernstein operators via an adaptation of Bézier bases which are formulated with the inclusion of the shape parameters
,
, and a positive parameter
First, we present a uniform convergence result for these operators and, subsequently, examine the convergence properties by utilizing the weighted
-statistical convergence notion. Furthermore, we estimate the rate of the weighted
-statistical convergence of these operators. We conclude our work by providing a numerical example with explanatory graphs to show their approximation behaviours.
1. Introduction
In the field of mathematical analysis, the Weierstrass Approximation Theorem (Weierstrass Citation1885) has immense significance since it states that any continuous function on a closed and bounded interval can be uniformly approximated on that interval by a sequence of polynomials
within a bounded error. Consequently, there have been different approaches to the statement and the proof of the Weierstrass Approximation Theorem. In 1912, one of the most famous advances to prove this landmark theorem was implemented by Sergei N. Bernstein (Citation1912) via the so-called Bernstein polynomials. In order to achieve his goal, Bernstein (Citation1912) defined the following Bernstein operators
where
and
are the Bernstein basis functions. Bernstein-type operators have attracted great attention due to their invaluable traits listed below:
They have explicit forms and operate competently for the functions which are well-defined for rational-valued variables.
They possess numerous shape-preserving properties, such as linearity, monotonicity, endpoint interpolation, and convexity.
These operators, along with their variations, are easy to manipulate in computer programs and very convenient to work with if the structure of the function is intricate.
They have many crucial and impressive implementations in the fields of signal and image processes, solutions of differential and integral equations, robotics, and so on.
Even though they satisfy the Korovkin theorem in the classical sense, they also fulfill the different versions of Korovkin theorems which utilize the summability methods and statistical type convergences since they are well connected with the theory of infinite matrices and summability.
Because of these traits mentioned above, there has been tremendous research done regarding the approximation and shape-preserving properties, along with many other aspects of the Bernstein operators and their variations in the last century. Two of the most notable variations of classical Bernstein operators (1.1) were introduced by Kantorovich and Stancu in (Citation1930) and (Stancu Citation1968), respectively. The operators defined by Kantorovich, denoted as , are an integral adaptation of operators in (1.1) and very convenient tools to approximate functions that are Riemann integrable on
The operators symbolized as
which are inaugurated by Stancu, involve two real parameters
and
with
The purpose here was to give more flexibility in modelling with the inclusion of parameters
and
One can find more information on these operators and the subsequent studies in papers (Cai et al. Citation2022; Ayman Mursaleen et al. Citation2023, Citation2024; Bărbosu Citation2004; Bustamante Citation2017; Cai et al. Citation2018; Milovanović et al. Citation2018; Nasiruzzaman et al. Citation2019; Mohiuddine and Özger Citation2020; Özger Citation2019, Citation2020; Özger et al. Citation2020, Citation2022; Kadak and Özger Citation2021; Aktuğlu et al. Citation2022; Ansari et al. Citation2022a, Citation2022b; Aslan Citation2022, Citation2023, Citation2024; Bodur et al. Citation2022; Savaş and Mursaleen Citation2023; Srivastava et al. Citation2021) (and references therein), respectively.
Likewise, the Bernstein basis functions given in (2) have also been modified in order to achieve improved results on the surface and curve modellings. The one variation that intrigued us the most is called Bézier bases which were constructed by Ye et al. in (Ye et al. Citation2010) with the inclusion of shape parameter In a similar fashion, Chen et al. (Chen et al. Citation2017) defined the
version of bases in (1.2) where
, and subsequently, Gezer et al. (Citation2022) constructed the blending-type
-Bernstein operators by combining the shape parameters
, and
where
is a positive integer.
Gezer et al. defined the blending-type Bernstein operators by employing the sample values of
on the interval
Inspired by their work, we define the Kantorovich-Stancu type
Bernstein operators (
-BKSO) by taking into account the mean values of
in the intervals
, where
instead of sample values of
In this paper, we aim to investigate the approximation and convergence properties of
-BKSO in the statistical sense. Moreover, we give an estimation of the rate of weighted
-statistical convergence and prove a Voronovskaja-type approximation theorem by a family of linear operators using the notion of weighted
-statistical convergence.
The manuscript’s organization is as follows: Section 2 summarizes the variations of Bernstein-type operators. Section 3 is devoted to the construction of -BKSO and the auxiliary results regarding their moments, while section 4 provides our main results about the convergence properties of
-BKSO. Section 5 includes the explanatory figures, which show the approximation behaviour of
-BKSO and concluding remarks on our findings.
2. Essential preliminaries
In this section, we present the established work from the literature for the readers who are not familiar with the definitions of -Bernstein,
-Bernstein, blending
-Bernstein basis functions, and their corresponding operators. Firstly we note that the binomial coefficients are given by the formula
In (Chen et al. Citation2017), Chen et al. inaugurated a new type of operator, the so-called Bernstein operator, in the literature, which is given by
where real number is the shape parameter. For
and
the
Bernstein basis is represented by
,
and
If one chooses , then (3) reduces to the classical Bernstein operators given by (1). This implies that the
Bernstein operator is more efficient than the classical Bernstein operator. There are a vast number of studies built on the
Bernstein operators in the literature (see (Mohiuddine and Özger Citation2020; Aktuğlu et al. Citation2022; Chen et al. Citation2022) and references therein).
A decade ago, Ye et al. constructed the new Bézier bases with shape parameter by
where are defined as in (2) (see (Ye et al. Citation2010)). Later on, Cai et al. (Citation2018) established the corresponding
Bernstein operators as
Note that for Bézier bases in (4) and
Bernstein operators in (5) transform to the classical Bernstein bases and operators given by (2) and (1), respectively.
Next, we give the following lemma, which gives the moments of the Bernstein operators.
Lemma 1
([14]). For Bernstein operators, the following equalities hold true:
Recently, generalized blending-type -Bernstein operators, which utilize shape parameters
and
are constructed by Aktuğlu et al. in (Citation2022) as
for and
for , where
and
. The choices of
and
in operators (6) and (7) result in the classical Bernstein operators and
Bernstein operators given by (1) and (3), respectively.
Subsequently, in (Gezer et al. Citation2022) introduced the blending-type -Bernstein operators to the literature as follows:
where
is a positive integer and
are the blending-type -Bernstein bases with
defined as in (4). Note that
reduces to the classical Bernstein operators if
and
the
Bernstein operators if
and
the
Bernstein operators if
and
and lastly the blending-type
Bernstein operators if
.
For the sake of more precise and straightforward computations, Gezer et al. reformulated the blending-type -Bernstein operators given in Equation (8) in the following manner.
Theorem 1
([23]). For any
and a positive integer
,
and
Next, we give the following lemmas, which present the moments of the blending-type -Bernstein operators.
Lemma 2
([23]). If for any
and
we have
where
are defined as in equation (5) and have the moments given as in Lemma 1.
Lemma 3
([23]). If , for any
and
, we have the following identities:
Remark 1. In (Gezer et al. Citation2022), Gezer et al. only presented and proved the moments given by (10), (11) and (12) for In the next lemma, we will complete the unfinished part of Lemma 3 by stating and giving the proofs of
and
.
Lemma 4.
If , for any
and
, we have the moments
and
as follows:
Proof.
Recall that
by Theorem 1 when . Hence, it is sufficient to calculate
, since
is already given in Lemma 1. Therefore, for
we have
where
(see (Gezer et al. Citation2022)), and
By substitution of and
in
we get
Hence, by equations (2.13), (2.14) and Lemma 1, we obtain as in equation (2.11).
Next, we will compute First we need to obtain
For
we have
where
If we substitute , and
in
we obtain
Hence, by equations (2.13), (2.15) and Lemma 1, we attain as in equation (2.12). This completes the proof.
3. New (α, λ, s) – Bernstein-Kantorovich-Stancu operators of blending-type
This section is dedicated to the establishment and the associated auxiliary results of the operators Let
denote the space of all Lebesgue integrable functions on the interval
. Considering two non-negative parameters
and
such that
we construct the positive
-BKSO as
where and
are shape parameters,
and
are as in (9).
Remark 2.
Recall that for , the blending-type
-Bernstein bases are equal to Bézier bases, that is,
by identity (9). Therefore,
-BKSO given by (17) transform to
-Bernstein-Kantorovich-Stancu operators
introduced by Bodur et al. in (Citation2022). They gave a uniform convergence result along with the order of approximation in the sense of local approximation and Voronovskaja type theorem with a complete proof for operators
. Even though the moments for the case
were presented in (Bodur et al. Citation2022), we provide the proofs for these identities for the readers’ convenience.
Lemma 5.
Let
, and
. For
the moments of
-BKSO are as follows:
Proof.
By utilizing the definitions of the operators and
given in (17) and (8), respectively, we have the first three moments of
as
and
Recall that for we have
by Lemma 2. Bearing in mind this fact, we obtain the first three moments of
given in equations (3.2), (3.3) and (3.4) as
respectively. The proofs of equations (3.5) and (3.6) are omitted due to the similarity to the above calculations. Hence, the proof is complete.
Lemma 6.
Let
, and
. For
the moments of
-BKSO are as follows:
Proof.
We will again only derive the first three moments of for
since the remaining moments given in (3.10) and (3.11) are computed in the same way with the help of Lemma 4.
Now, by employing the definitions given in (3.1), (2.6) and Lemma 3, we obtain equations (3.7), (3.8) and (3.9) as
and
respectively, which completes the proof.
Corollary 1.
Let
and
. For
the central moments of
-BKSO are as follows:
Corollary 2.
Let
and
. For
the central moments of
-BKS operators are as follows
Lemma 7.
Let be the uniform norm defined on
and
Then for a given
for all and
Proof.
By taking into account Lemma 5, Lemma 6 and the definition of given in (3.1), we have
which concludes the proof.□
Theorem 2.
If is continuous on
, then
uniformly on
Proof.
Utilizing the well-known Bohman-Korovkin theorem (Korovkin Citation1960, Bohman Citation1952), our objective is to prove the subsequent condition for uniform convergence:
and the proof is completed.
Before we proceed with the following theorem, we shall note that refers to the set of functions
which are twice differentiable with
.
Theorem 3.
Assume that If
exists for a point
then
uniformly on
Proof.
Consider the case For a fixed
suppose that
. Due to Taylor’s expansion with a reminder in Peano’s form, we can write
Multiplication of both sides of (3.19) by and utilization of the Cauchy-Schwarz inequality, respectively, yield
Consequently, by fourth order central moment (34) and Theorem 2, and the following expression
we have
Hence, by (3.12), (3.13), (3.15) and (3.16), the proof is completed for Using the same techniques and following likewise steps, one can prove the statement for
; therefore, it is omitted.□
4. Convergence Results for Kantorovich-Stancu Type (α, λ, s)-Bernstein Operators ![](//:0)
![](//:0)
In this section, we investigate the convergence characteristics and a Voronovskaja type approximation result for -BKSO by utilizing the weighted
-statistical convergence notion. In addition, we give an estimation for the rate of the weighted
-statistical convergence of these operators. For the readers who are not familiar with the concepts of asymptotic density, statistical convergence, weighted statistical convergence,
-summability, regular summability matrix,
-statistically convergence, and weighted
-statistically convergence, we refer to pioneering works (Kadak et al. Citation2017; Kadak Citation2020) and the references therein. The application of Bohmann-Korovkin theorem using the weighted statistical convergence is studied in the papers (Mursaleen et al. Citation2012; Belen and Mohiuddine Citation2013; Mohiuddine Citation2016; Baliarsingh et al. Citation2018; Kadak Citation2018).
We begin our work by considering the set , a subset of
. The asymptotic density of the set
is denoted by
and is defined by
provided the limit exists. Note that asymptotic density lets us define the statistical convergence. Consequently, we say a sequence is statistically convergent to the number
if
Next, consider a sequence of non-negative numbers denoted given with
If
then we say is weighted statistically convergent to the number
. Kolk (Kolk Citation1993) introduced a new matrix method, so-called
-summability as follows:
Let be a sequence of infinite matrices. If
for , then we say
is
-summable to the value
. The method
is said to be regular if and only if the below conditions are satisfied (see (Stieglitz Citation1973; Bell Citation1973)):C1:
C2: for
;
C3:
The set of regular methods satisfying
for all
,
, and
is denoted by
. For a given
, if
for all , then we say
is
-statistically convergent to the number
.
Definition 1
([33]). Assume that and let sequence
be defined as in (37). If
for all and
, then the sequence
is weighted
-statistically convergent to the number
. In symbols, it is written as
.
Theorem 4.
Let
and
. Then we have
for all and positive integer
Proof.
For , let
and consider a sequence of functions
for a fixed
It is enough to show that
on the grounds of Korovkin-Bohman Theorem (see (Bohman Citation1952; Korovkin Citation1960)). Accordingly for we obtain
by employing identity (3.7) from Lemma 6. Now for by substitution of identities (3.8) and (3.15) respectively, we get
which implies
Next, for a fixed we choose a number
such that
. Subsequently, defining the sets
and
as follows
we attain
Taking in inequality (4.3) yields
Last, for we can write
by utilizing identities (3.9) and (3.16) respectively. In a similar fashion to the preceding case, we can deduce that
Hence, the proof is complete for due equations (4.2), (4.4) and (4.5). The proof of the assertion for
is omitted since it is tantamount to the proof of the case
.□
Definition 2
([24]). Assume that . If
for all , then we say
is statistically weighted
-summable to the limit value
. In symbols, it is written as
.
Theorem 5
([24]). A bounded sequence ,
, is statistically weighted
-summable to the number
if it is weighted
-statistically convergent to the same number
. However, the reverse is not true.
We deduce the next corollary due to Theorem 4 and Theorem 5.
Corollary 3.
For and
, we have
Now, we are ready to give an estimation for the rate of the weighted -statistical convergence of
-BKSO to
via modulus of continuity of first order. First, we shall present the definition regarding the weighted
-statistical convergence of positive and non-decreasing sequences, which we will utilize in the theorem that follows.
Definition 3
([24]). Let and assume that
is a non-decreasing and positive sequence. If
for any , then we say sequence
is weighted
-statistically convergent to limit
with the rate
. In symbols, it is written as
Theorem 6.
Let be a non-negative regular summability matrix and
be a non-decreasing and positive sequence. If the condition
on
, where
with
holds true, then for
where is the usual modulus of continuity.
Proof.
For fixed assume that
. Linearity of
-BKSO implies
where Subsequently, considering the supremum over
for (4.6) and letting
, one obtains
The following sets are defined or a given as
Here one may easily verify that
Last, by employing the given condition the theorem is proved.□
Our next goal is to obtain a quantitative Voronovskaja-type result for the -BKSO,
with the help of first-order Ditzian-Totik modulus of smoothness (see (Ditzian and Totik Citation1987)). The first-order Ditzian-Totik modulus of smoothness of a function
is defined as
where ,
and
Let denote the class of absolutely continuous functions defined on
Also, for any
let
be the set of all such
satisfying
and
. Then, we define the corresponding
-functional of
by
In (Ditzian and Totik Citation1987), Ditzian and Totik proved that
for some constants and
We hall note that
is independent of
and
.
Theorem 7.
Let and constant
be defined as in (4.8). Moreover, define the terms
and
as
Then for all and
, we have
Proof.
For consider the function
. If we apply Taylor’s formula to function
, we obtain
Subsequently, we can write
Next, utilization of -BKSO to both sides of (4.9) yields
Inspired by (Finta Citation2011), we can estimate the quantity on the right-hand side of (4.10) as
where . Then utilizing identities (3.16) and (3.17) from Corollary 2 for
, we get
Consequently, we conclude
by combining inequalities (4.10)–(4.11) and using the Cauchy-Schwarz inequality. Lastly, we get
by taking the infimum of the right-hand side of (4.12) over all □
The next corollary directly results from Theorem 7.
Corollary 4.
For and
, we have
5. Conclusions with numerical results
In our manuscript, we introduced the operators with the inclusion of the shape parameters
and a positive parameter
. We presented a uniform convergence result and analysed the convergence properties of
. In addition, we gave a Voronovskaja-type approximation result with the help of the weighted
statistical convergence notion and estimated the rate of the weighted
statistical convergence of these operators.
Now, to observe the approximation behaviour of the operators we consider the function
From , we can easily say that
behaves consistently with the given function
and we observe that approximation behaviour of
shows improvement since an error in the calculations decreases as
value increases (see ). Furthermore, presents the absolute errors for
, the
Bernstein operator
given in (2.1), the Stancu variant of
Bernstein-Kantorovich operators
constructed in (Mohiuddine and Özger Citation2020) and the Kantorovich variant of modified Bernstein operators
introduced in (Gupta et al. Citation2019), respectively. It can be deduced from that
gives a better approximation for the given function
compared to the operators
and
Due to the inclusion of shape parameters
and the positive parameter
together within the basis function, it is clear to see that the operators
are a generalization of the other operators from the literature, which are listed in . It is imperative to note that it is possible to enhance the approximation behaviour of operators
by altering their bases functions or taking the linear and repetitive combinations of the mentioned operators. For example, the
modification of these operators can be examined as future work.
Table 1. Absolute errors for the operators ,
,
, and
for
when
,
,
and
.
Table 2. Reduction of the operators for specific values of the various parameters.
Acknowledgments
The authors have greatly benefitted from the constructive feedback of the editor and anonymous referees. Therefore, they express their gratitude for the valuable comments provided on the initial draft of this paper, which contributed to enhancing its presentation and readability.
Disclosure statement
No potential conflict of interest was reported by the author(s).
References
- Acu AM, Manav N, Sofonea DF. 2018. Approximation properties of λ-Kantorovich operators. J Inequal Appl. 2018(1):Article ID 202. doi: 10.1186/s13660-018-1795-7.
- Aktuğlu H, Gezer H, Baytunç E, Atamert MS. 2022. Approximation properties of generalized blending type lototsky-Bernstein operators. J Math Inequal. 16(2):707–728. doi: 10.7153/jmi-2022-16-50.
- Ansari KJ, Karakılıç S, Özger F. 2022a. Bivariate Bernstein-kantorovich operators with a summability method and related GBS operators. Filomat. 36(19):6751–6765. doi: 10.2298/FIL2219751A.
- Ansari KJ, Özger F, Ödemiş Özger Z. 2022b. Numerical and theoretical approximation results for schurer-stancu operators with shape parameter λ. Comp Appl Math. 41(4):1–18. doi: 10.1007/s40314-022-01877-4.
- Aslan R. 2022. On a stancu form szász-mirakjan-kantorovich operators based on shape parameter λ. Adv Studies: Euro-Tbilisi Math J. 15(1):151–166. doi: 10.32513/asetmj/19322008210.
- Aslan R. 2023. Approximation properties of univariate and bivariate new class $\lambda $-Bernstein–Kantorovich operators and its associated GBS operators. Comp Appl Math. 42(1):Article ID 34. DOI. doi: 10.1007/s40314-022-02182-w.
- Aslan R. 2024. Rate of approximation of blending type modified univariate and bivariate λ-Schurer-Kantorovich operators. Kuwait J Sci. 51(1):100168. doi: 10.1016/j.kjs.2023.12.007.
- Ayman-Mursaleen M, Nasiruzzaman M, Rao N, Dilshad M, Nisar KS. 2024. Approximation by the modified $ \lambda $-Bernstein-polynomial in terms of basis function. Math. 9(2):4409–4426. doi: 10.3934/math.2024217.
- Ayman-Mursaleen M, Rao N, Rani M, Kilicman A, Al-Abied AA, Malik P, Gobithaasan RU. 2023. A Note on Approximation of Blending Type Bernstein–Schurer–Kantorovich Operators with Shape Parameter α. J Math. 2023:1–13. doi: 10.1155/2023/5245806.
- Baliarsingh P, Kadak U, Mursaleen M. 2018. On statistical convergence of difference sequences of fractional order and related Korovkin type approximation theorems. Quaest Math. 41(8):1117–1133. doi: 10.2989/16073606.2017.1420705.
- Bărbosu D. 2004. Kantorovich-Stancu type operators. J Inequal Pure Appl Math. 5(3):1–6. doi: 10.18514/MMN.2004.71.
- Belen C, Mohiuddine SA. 2013. Generalized weighted statistical convergence and application. Appl Math Comput. 219(18):9821–9826. doi: 10.1016/j.amc.2013.03.115.
- Bell HT. 1973. Order summability and almost convergence. Proc Amer Math Soc. 38(3):548–552. doi: 10.1090/S0002-9939-1973-0310489-8.
- Bernstein S. 1912. Dámonstration du tháorème de Weierstrass fondeá sur le calcul des probabilitás. Commun Soc Math Kharkow. 13(1):1–2.
- Bodur M, Manav N, Tasdelen F. 2022. Approximation properties of λ-Bernstein-kantorovich-stancu operators. Math Slovaca. 72(1):141–152. doi: 10.1515/ms-2022-0010.
- Bohman H. 1952. On approximation of continuous and of analytic functions. Ark Mat. 2(1):43–56. doi: 10.1007/BF02591381.
- Bustamante J. 2017. Bernstein operators and their properties. Cham: Springer. doi:10.1007/978-3-319-55402-0.
- Cai Q, Ansari KJ, Temizer Ersoy M, Özger F. 2022. Statistical Blending-Type Approximation by a Class of Operators That Includes Shape Parameters λ and α. Math. 10(7):1149. doi: 10.3390/math10071149.
- Cai QB, Lian BY, Zhou G. 2018. Approximation properties of λ-Bernstein operators. J Inequal Appl. 2018(61):1–11. doi: 10.1186/s13660-018-1653-7.
- Chen M-Y, Nasiruzzaman M, Mursaleen MA, Rao N, Kiliçman A. 2022. On shape parameter α based approximation properties and q-statistical convergence of baskakov-gamma operators. Jour Mathematics. 2022:4190732. https://www.hindawi.com/journals/jmath/2022/4190732.
- Chen X, Tan J, Liu Z, Xie J. 2017. Approximation of functions by a new family of generalized Bernstein operators. J Math Anal Appl. 450(1):244–261. doi: 10.1016/j.jmaa.2016.12.075.
- Ditzian Z, Totik V. 1987. Moduli of Smoothness. In: Springer series in computational mathematics. Vol. 9, New York, NY: Springer-Verlag. doi: 10.1007/978-1-4612-4778-4.
- Finta Z. 2011. Remark on Voronovskaja theorem for q-Bernstein operators. Stud Univ Babeş-Bolyai Math. 56(2):335–339.
- Gezer H, Aktuğlu H, Baytunç E, Atamert MS. 2022. Generalized blending type Bernstein operators based on the shape parameter λ. J Inequal Appl. 2022(96):1–19. doi: 10.1186/s13660-022-02832-x.
- Gupta V, Tachev G, Acu AM. 2019. Modified Kantorovich operators with better approximation properties. Numer Algor. 81(1):125–149. doi: 10.1007/s11075-018-0538-7.
- Kadak U. 2018. Modularly weighted four dimensional matrix summability with application to Korovkin type approximation theorem. J Math Anal Appl. 468(1):38–63. doi: 10.1016/j.jmaa.2018.06.047.
- Kadak U. 2020. Statistical summability of double sequences by the weighted mean and associated approximation results. In: Dutta H, Peters J, editors. Applied mathematical analysis: theory, methods, and applications. Cham: Springer; pp. 61–85.
- Kadak U, Braha NL, Srivastava HM. 2017. Statistical weighted B-summability and its applications to approximation theorems. Appl Math Comput. 302:80–96. doi: 10.1016/j.amc.2017.01.011.
- Kadak U, Özger F. 2021. A numerical comparative study of generalized Bernstein-kantorovich operators. Math Found Comput. 4(4):311–332. doi: 10.3934/mfc.2021021.
- Kantorovich LV. 1930. Sur certains developpements suivant les polynômes de la forme de S.Bernstein I, II. Dokl Akad Nauk SSSR. 563–568, 595–600.
- Kolk E. 1993. Matrix summability of statistically convergent sequences. Analysis. 13(1–2):77–83. doi: 10.1524/anly.1993.13.12.77.
- Korovkin PP. 1960. Linear operators and approximation theory. Delhi, India: Hindustan Publishing Corporation.
- Milovanović GV, Mursaleen M, Nasiruzzaman M. 2018. Modified Stancu type dunkl generalization of szász–Kantorovich operators. RACSAM. 112(1):135–151. doi: 10.1007/s13398-016-0369-0.
- Mohiuddine SA. 2016. Statistical weighted A-summability with application to Korovkin’s type approximation theorem. J Inequal Appl. 2016(1):Article ID 101. doi: 10.1186/s13660-016-1040-1.
- Mohiuddine SA, Acar T, Alotaibi A. 2017. Construction of a new family of Bernstein-Kantorovich operators. Math Meth Appl Sci. 40(18):7749–7759. doi: 10.1002/mma.4559.
- Mohiuddine SA, Özger F. 2020. Approximation of functions by Stancu variant of Bernstein–Kantorovich operators based on shape parameter ${\varvec{\alpha}}$. RACSAM. 114(2):Article ID 70. doi: 10.1007/s13398-020-00802-w.
- Mursaleen M, Karakaya V, Ertürk M, Gürsoy F. 2012. Weighted statistical convergence and its application to Korovkin type approximation theorem. Appl Math Comput. 218(18):9132–9137. doi: 10.1016/j.amc.2012.02.068.
- Nasiruzzaman M, Rao N, Wazir S, Kumar R. 2019. Approximation on parametric extension of baskakov–durrmeyer operators on weighted spaces. J Inequal Appl. 2019(1):Article ID 103. doi: 10.1186/s13660-019-2055-1.
- Özger F. 2019. Weighted statistical approximation properties of univariate and bivariate λ-Kantorovich operators. Filomat. 33(11):3473–3486. doi: 10.2298/FIL1911473O.
- Özger F. 2020. Applications of Generalized Weighted Statistical Convergence to Approximation Theorems for Functions of One and Two Variables. Numer Funct Anal Optim. 41(16):1990–2006. doi: 10.1080/01630563.2020.1868503.
- Özger F, Aljimi E, Temizer Ersoy M. 2022. Rate of weighted statistical convergence for generalized blending-type Bernstein-kantorovich operators. Mathematics. 10(12):Article ID 2027. doi: 10.3390/math10122027.
- Özger F, Demirci K, Yıldız S. 2020. Approximation by Kantorovich variant of λ-schurer operators and related numerical results. In: Dutta H, editor. Topics in contemporary mathematical analysis and applications. Boca Raton: CRC Press; p. 77–94. ISBN 9780367532666.
- Savaş E, Mursaleen M. 2023. Bézier Type Kantorovich q-Baskakov Operators via Wavelets and Some Approximation Properties. Bull Iran Math Soc. 49(5). doi: 10.1007/s41980-023-00815-2.
- Srivastava HM, Ansari KJ, Özger F, Ödemiş Özger Z. 2021. A Link between Approximation Theory and Summability Methods via Four-Dimensional Infinite Matrices. Math. 9(16):1895. doi: 10.3390/math9161895.
- Stancu DD. 1968. Approximation of function by a new class of polynomial operators. Rev Roum Math Pures Appl. 13(8):1173–1194.
- Stieglitz M. 1973. Eine verallgemeinerung des begriffs der fastkonvergenz. Math Japon. 18(1):53–70.
- Weierstrass VK. 1885. Über die analytische Darstellbarkeit sogenannter willkürlicher Functionen einer reellen Veränderlichen. Sitzungsberichte der Königlich Preuß ischen Akademie der Wissenschaften zu Berlin. 2:633–639.
- Ye Z, Long X, Zeng XM, Adjustment algoritheorems for bézier curve and surface, in: The 5. International Conference on Computer Science and Education, 2010, 1712–1716. doi: 10.1109/ICCSE.2010.5593563