# On Equivalence of Some Iterations Convergence for Quasi-Contraction Maps in Convex Metric Spaces

- Zhiqun Xue
^{1}Email author, - Guiwen Lv
^{1}and - BE Rhoades
^{2}

**2010**:252871

https://doi.org/10.1155/2010/252871

© Zhiqun Xue et al. 2010

**Received: **23 July 2010

**Accepted: **9 September 2010

**Published: **19 September 2010

## Abstract

We show the equivalence of the convergence of Picard and Krasnoselskij, Mann, and Ishikawa iterations for the quasi-contraction mappings in convex metric spaces.

## 1. Introduction

*W*is said to be a convex structure on [1] if for all with such that

If satisfies the conditions of convex structure, then is called convex metric space that is denoted as .

In the following part, we will consider a few iteration sequences in convex metric space . Suppose that is a self-map of .

Combining above three definitions, Zamfirescu [4] showed the following result.

Theorem 1.1.

Let be a complete metric space and a mapping for which there exist the real numbers and satisfying such that, for any pair , at least one of the following conditions holds:

Then has a unique fixed point, and the Picard iteration converges to fixed point. This class mapping is called Zamfirescu mapping.

Clearly, every quasi-contraction mapping is the most general of above mappings.

Later on, in 1992, Xu [6] proved that Ishikawa iteration can also be used to approximate the fixed points of quasi-contraction mappings in real Banach spaces.

Theorem 1.2.

Let be any nonempty closed convex subset of a Banach space and a quasi-contraction mapping. Suppose that for all and . Then the Ishikawa iteration sequence defined by (1)–(3) converges strongly to the unique fixed point of .

In this paper, we will show the equivalence of the convergence of Picard and Krasnoselskij, Mann, and Ishikawa iterations for the quasi-contraction mappings in convex metric spaces.

Lemma 1.3.

where , and as . Then as (see [7]).

## 2. Results for Quasi-Contraction Mappings

Theorem 2.1.

Let be a convex metric space, a quasi-contraction mapping with . Suppose that are defined by the iterative processes (1.3) and (1.4), respectively. Then, the following two assertions are equivalent:

(i)Picard iteration (1.3) converges strongly to the unique fixed point ;

(ii)Krasnoselskij iteration (1.4) converges strongly to the unique fixed point .

Proof.

First, we show , that is, as as .

Then is bounded. Without loss of generality, we let for each . Indeed, we will show this conclusion from the some following cases.

and it leads to a contradiction. Thus, . Similarity to or is also impossible.

it implies that . By induction on , we can get .

it implies that , and by induction on , we may get , which is a contradiction.

it implies that and by induction on , then .

(ii)If , then, from (1.3) and (1.10)

this is a contradiction.

it is a contradiction.

which is a contradiction.

In view of the above cases, then , and we obtain that is bounded.

which implies that . Similarly, if or , we also obtain .

which implies that . Similarly, if or , we also obtain . Therefore, from the above results, we obtain that , that is, is bounded.

By Lemma 1.3, we have as . From the inequality , we have .

Conversely, we will prove that . If , then is Picard iteration.

Theorem 2.2.

Let be as in Theorem 2.1. Suppose that are defined by the iterative processes (1.5) and (1.6), respectively, and are real sequences in such that . Then, the following two assertions are equivalent:

(i)Mann iteration (1.5) converges strongly to the unique fixed point ;

(ii)Ishikawa iteration (1.6) converges strongly to the unique fixed point .

Proof.

If the Ishikawa iteration (1.6) converges strongly to , then setting , in (1.6), we can get the convergence of Mann iteration (1.5). Conversely, we will show that . Letting , we want to prove .

Applying the similar proof methods of Theorem 2.1, we obtain that is also bounded. The other proof is the same as that of Theorem 2.1 and is here omitted.

## Declarations

### Acknowledgments

The authors are extremely grateful to Professor B. E. Rhoades of Indiana University for providing useful information and many help. They also thank the referees for their valuable comments and suggestions.

## Authors’ Affiliations

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## Copyright

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