# A New Estimate on the Rate of Convergence of Durrmeyer-Bézier Operators

- Pinghua Wang
^{1}Email author and - Yali Zhou
^{2}

**2009**:702680

**DOI: **10.1155/2009/702680

© P.Wang and Y. Zhou. 2009

**Received: **20 February 2009

**Accepted: **13 April 2009

**Published: **5 May 2009

## Abstract

We obtain an estimate on the rate of convergence of Durrmeyer-Bézier operaters for functions of bounded variation by means of some probabilistic methods and inequality techniques. Our estimate improves the result of Zeng and Chen (2000).

## 1. Introdution

In 2000, Zeng and Chen [1] introduced the Durrmeyer-Bézier operators which are defined as follows:

where is defined on , , , , are Bézier basis functions, and , are Bernstein basis functions.

When , is just the well-known Durrmeyer operator

Concerning the approximation properties of operators and some results on approximation of functions of bounded variation by positive linear operators, one can refer to [2–7]. Authors of [1] studied the rate of convergence of the operators for functions of bounded variation and presented the following important result.

Theorem A

Let be a function of bounded variation on , ( ), then for every and one has

Since the Durrmeyer-Bézier operators are an important approximation operator of new type, the purpose of this paper is to continue studying the approximation properties of the operators for functions of bounded variation, and give a better estimate than that of Theorem A by means of some probabilistic methods and inequality techniques. The result of this paper is as follows.

Theorem 1.1.

Let be a function of bounded variation on , ( ), then for every and one has

It is obvious that the estimate (1.5) is better than the estimate (1.3). More important, the estimate (1.5) is true for all . This is an important improvement comparing with the fact that estimate (1.3) holds only for .

## 2. Some Lemmas

In order to prove Theorem 1.1, we need the following preliminary results.

Lemma 2.1.

Proof.

The inequality (2.1) is proved.

we get the inequality (2.2). Lemma 2.1 is proved.

Lemma 2.2.

Proof.

Thus Lemma 2.2 is proved.

## 3. Proof of Theorem 1.1

Let satisfy the conditions of Theorem 1.1, then can be decomposed as

Obviously thus from (3.1) we get

We first estimate , from [1, page 11] we have the following equation:

Thus by Lemma 2.2, we get . Note that , we have

Next we estimate . From (15) of [1], it follows the inequality

That is,

On the other hand, note that , we have

From (3.7) and (3.8) we obtain

Using inequality

we get

Thus from (3.9) we obtain

Theorem 1.1 now follows by collecting the estimations (3.3), (3.5), and (3.12).

## Declarations

### Acknowledgment

The present work is supported by Project 2007J0188 of Fujian Provincial Science Foundation of China.

## Authors’ Affiliations

## References

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## Copyright

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