Abstract
In this paper, we introduce a new type λ-Bernstein operators with parameter , we investigate a Korovkin type approximation theorem, establish a local approximation theorem, give a convergence theorem for the Lipschitz continuous functions, we also obtain a Voronovskaja-type asymptotic formula. Finally, we give some graphs and numerical examples to show the convergence of to , and we see that in some cases the errors are smaller than to f.
Keywords: λ-Bernstein operators, Bézier basis functions, Modulus of continuity, Lipschitz continuous functions, Voronovskaja asymptotic formula
Introduction
In 1912, Bernstein [1] proposed the famous polynomials called nowadays Bernstein polynomials to prove the Weierstrass approximation theorem as follows:
| 1 |
where , , and Bernstein basis functions are defined as:
| 2 |
Based on this, there are many papers about Bernstein type operators [2–9]. In 2010, Ye et al. [10] defined new Bézier bases with shape parameter λ by
| 3 |
where . When , they reduce to (2). It must be pointed out that we have more modeling flexibility when adding the shape parameter λ.
In this paper, we introduce the new λ-Bernstein operators,
| 4 |
where () are defined in (3) and .
This paper is organized as follows: In the following section, we estimate the moments and central moments of these operators (4). In Sect. 3, we investigate a Korovkin approximation theorem, establish a local approximation theorem, give a convergence theorem for the Lipschitz continuous functions, and obtain a Voronovskaja-type asymptotic formula. In Sect. 4, we give some graphs and numerical examples to show the convergence of to with different parameters.
Some preliminary results
Lemma 2.1
For λ-Bernstein operators, we have the following equalities:
| 5 |
| 6 |
| 7 |
| 8 |
| 9 |
Proof
From (4), it is easy to prove , then we can obtain (5). Next,
as is well known, the Bernstein operators (1) preserve linear functions, that is to say, . We denote the latter two parts in the bracket of the last formula by and , then we have
| 10 |
Now, we will compute and ,
| 11 |
and
| 12 |
Combining (10), (11) and (12), we have
Hence, (6) is proved. Finally, by (4), we have
since , and we denote the latter two parts in the bracket of last formula by and , then we have
| 13 |
On the one hand,
| 14 |
On the other hand,
| 15 |
Combining (13), (14) and (15), we obtain
therefore, we get (7). Thus, Lemma 2.1 is proved.
Similarly, we can obtain (8) and (9) by some computations, here we omit these. □
Corollary 2.2
For fixed and , using Lemma 2.1 and by some easy computations, we have
| 16 |
| 17 |
| 18 |
| 19 |
| 20 |
Remark 2.3
For , , λ-Bernstein operators possess the endpoint interpolation property, that is,
| 21 |
Proof
We can obtain (21) easily by using the definition of λ-Bernstein operators (4) and
Remark 2.3 is proved. □
Example 2.4
The graphs of with are shown in Fig. 1(left). The corresponding with are shown in Fig. 1(right). The graphs show the λ-Bernstein operators’ endpoint interpolation property, which is based on the interpolation property of .
Figure 1.

The graphs of with different values of λ (left) and their corresponding (right)
Convergence properties
As we know, the space of all continuous functions on is a Banach space with sup-norm . Now, we give a Korovkin type approximation theorem for .
Theorem 3.1
For , , λ-Bernstein operators converge uniformly to f on .
Proof
By the Korovkin theorem it suffices to show that
We can obtain these three conditions easily by (5), (6) and (7) of Lemma 2.1. Thus the proof is completed. □
The Peetre K-functional is defined by , where and . By [11], there exists an absolute constant such that
| 22 |
where is the second order modulus of smoothness of . We also denote the usual modulus of continuity of by .
Next, we give a direct local approximation theorem for the operators .
Theorem 3.2
For , , we have
| 23 |
where C is a positive constant, and are defined in (16) and (17).
Proof
We define the auxiliary operators
| 24 |
From (5) and (6), we know that the operators are linear and preserve the linear functions:
| 25 |
Let , by Taylor’s expansion,
and (25), we get
Hence, by (24) and (17), we have
On the other hand, by (24), (5) and (4), we have
| 26 |
Hence, taking infimum on the right hand side over all , we get
By (22), we have
where and are defined in (16) and (17). This completes the proof of Theorem 3.2. □
Remark 3.3
For any , we have and , these give us a rate of pointwise convergence of the operators to .
Now, we study the rate of convergence of the operators with the help of functions of Lipschitz class , where and . A function f belongs to if
| 27 |
We have the following theorem.
Theorem 3.4
Let , and , then we have
where is defined in (17).
Proof
Since are linear positive operators and , we have
Applying Hölder’s inequality for sums, we obtain
Thus, Theorem 3.4 is proved. □
Finally, we give a Voronovskaja asymptotic formula for .
Theorem 3.5
Let be bounded on . Then, for any at which exists, , we have
| 28 |
Proof
Let be fixed. By the Taylor formula, we may write
| 29 |
where is the Peano form of the remainder, , using L’Hopital’s rule, we have
Applying to (29), we obtain
| 30 |
By the Cauchy–Schwarz inequality, we have
| 31 |
since , then we can obtain
| 32 |
by (31) and (20). Finally, using (18), (19), (32) and (30), we get
Theorem 3.5 is proved. □
Graphical and numerical analysis
In this section, we give several graphs and numerical examples to show the convergence of to with different values of λ and n.
Let , the graphs of and with different values of n are shown in Figs. 2 and 3. In Table 1, we give the errors of the approximation of to . We can see from Table 1 that in some special cases (such as and ), the errors of are smaller than (where are classical Bernstein operators). Figure 4 shows the graphs of with and different values of λ.
Figure 2.

The graphs of with different values of n
Figure 3.

The graphs of with different values of n
Table 1.
The errors of the approximation of to with different values of n and λ
| λ | |||||
|---|---|---|---|---|---|
| n = 10 | n = 20 | n = 50 | n = 100 | n = 150 | |
| −1 | 0.437813 | 0.242921 | 0.104883 | 0.054106 | 0.036478 |
| −0.5 | 0.430221 | 0.241337 | 0.104880 | 0.054136 | 0.036496 |
| 0 | 0.422857 | 0.239850 | 0.104884 | 0.054166 | 0.036513 |
| 0.5 | 0.415719 | 0.238458 | 0.104897 | 0.054196 | 0.036531 |
| 1 | 0.408808 | 0.237158 | 0.104918 | 0.054229 | 0.036550 |
Figure 4.

The graphs of with different values of λ
Acknowledgements
This work is supported by the National Natural Science Foundation of China (Grant Nos. 11601266 and 11626201), the Natural Science Foundation of Fujian Province of China (Grant No. 2016J05017) and the Program for New Century Excellent Talents in Fujian Province University. We also thank Fujian Provincial Key Laboratory of Data Intensive Computing and Key Laboratory of Intelligent Computing and Information Processing of Fujian Province University.
Authors’ contributions
QBC, BYL and GZ carried out the molecular genetic studies, participated in the sequence alignment and drafted the manuscript. QBC, BYL and GZ carried out the immunoassays. QBC. BYL and GZ participated in the sequence alignment. QBC, BYL and GZ participated in the design of the study and performed the statistical analysis. QBC, BYL and GZ conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Footnotes
Publisher’s Note
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Contributor Information
Qing-Bo Cai, Email: qbcai@126.com.
Bo-Yong Lian, Email: lianboyong@163.com.
Guorong Zhou, Email: goonchow@xmut.edu.cn.
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