- Research Article
- Open Access
© Xiaolong Qin et al. 2010
- Received: 31 August 2009
- Accepted: 19 November 2009
- Published: 24 November 2009
- Hilbert Space
- Convex Subset
- Nonexpansive Mapping
- Nonempty Closed Convex Subset
- Real Sequence
where is a fixed element. Banach Contraction Mapping Principle guarantees that has a unique fixed point in . It is unclear, in general, what the behavior of is as even if has a fixed point. However, in the case of having a fixed point, Browder  proved the following well-known strong convergence theorem.
Theorem 1 B.
Motivated by Theorem B, Halpern  considered the following explicit iteration:
and obtained the following theorem.
Theorem 1 H.
Let be a bounded closed convex subset of a Hilbert space and a nonexpansive mapping on . Define a real sequence in by , . Then the sequence defined by (1.3) converges strongly to the element of nearest to .
In , Lions improved the result of Halpern , still in Hilbert spaces, by proving the strong convergence of to a fixed point of provided that the control sequence satisfies the following conditions:
It was observed that both the Halpern's and Lion's conditions on the real sequence excluded the canonical choice . This was overcome by Wittmann , who proved, still in Hilbert spaces, the strong convergence of to a fixed point of if satisfies the following conditions:
In , Shioji and Takahashi extended Wittmann's results to the setting of Banach spaces under the assumptions (C1), (C2), and (C4) imposed on the control sequences . In , Xu remarked that the conditions (C1) and (C2) are necessary for the strong convergence of the iterative sequence defined in (1.3) for all nonexpansive self-mappings. It is well known that the iterative algorithm (1.3) is widely believed to have slow convergence because the restriction of condition (C2). Thus, to improve the rate of convergence of the iterative process (1.3), one cannot rely only on the process itself.
Recently, hybrid projection algorithms have been studied for the fixed point problems of nonlinear mappings by many authors; see, for example, [8–24]. In 2006, Martinez-Yanes and Xu  proposed the following modification of the Halpern iteration for a single nonexpansive mapping in a Hilbert space. To be more precise, they proved the following theorem.
Theorem 1 MYX.
Theorem 1 QS.
In this paper, motivated by Kimura and Takahashi , Martinez-Yanes and Xu , Qin and Su , and Qin et al. , we consider a hybrid projection algorithm to modify the iterative process (1.3) to have strong convergence under condition (C1) only for a family of closed quasi- -nonexpansive mappings.
We know that, if is a nonempty closed convex subset of a Hilbert space and is the metric projection of onto , then is nonexpansive. This fact actually characterizes Hilbert spaces and, consequently, it is not available in more general Banach spaces. In this connection, Alber  recently introduced a generalized projection operator in a Banach space , which is an analogue of the metric projection in Hilbert spaces.
A Banach space is said to be strictly convex if for all with and . The space is said to be uniformly convex if for any two sequences and in such that and . Let be the unit sphere of . Then the space is said to be smooth if
exists for each It is also said to be uniformly smooth if the limit is attained uniformly for . It is well known that, if is uniformly smooth, then is uniformly norm-to-norm continuous on each bounded subset of .
Observe that, in a Hilbert space , (2.3) reduces to for all The generalized projection is a mapping that assigns to an arbitrary point the minimum point of the functional that is, where is the solution to the minimization problem:
The existence and uniqueness of the operator follows from some properties of the functional and the strict monotonicity of the mapping (see, e.g., [25–28]). In Hilbert spaces, It is obvious from the definition of the function that
If is a reflexive, strictly convex, and smooth Banach space, then, for any , if and only if . In fact, it is sufficient to show that, if , then . From (2.5), we have . This implies From the definition of one has . Therefore, we have (see [27, 29] for more details).
Let be a nonempty closed and convex subset of and a mapping from into itself. A point is said to be an asymptotic fixed point of () if contains a sequence which converges weakly to such that . The set of asymptotic fixed points of will be denoted by . A mapping from into itself is said to be relatively nonexpansive ([27, 31, 32]) if and for all and . The asymptotic behavior of a relatively nonexpansive mapping was studied by some authors ([27, 31, 32]).
In order to prove our main results, we need the following lemmas.
Lemma 2.3 (see ).
On the other hand, we have
Comparing the hybrid projection algorithm (3.1) in Theorem 3.1 with algorithm (1.5) in Theorem QS, we remark that the set is constructed based on the set instead of for each We obtain that the sequence generated by the algorithm (3.1) is a Cauchy sequence. The proof is, therefore, different from the one presented in Qin and Su .
Corollary 3.3 mainly improves Theorem of Qin and Su  from the class of relatively nonexpansive mappings to the class of quasi- -nonexpansive mappings, which relaxes the strong restriction:
In the framework of Hilbert spaces, Theorem 3.1 is reduced to the following result.
Corollary 3.5 includes the corresponding result of Martinez-Yanes and Xu  as a special case. To be more precise, Corollary 3.5 improves Theorem 3.1 of Martinez-Yanes and Xu  from a single mapping to a family of mappings and from nonexpansive mappings to quasi-nonexpansive mappings, respectively.
This work was supported by the Korea Research Foundation Grant funded by the Korean Government (KRF-2008-313-C00050).
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