Abstract
The CQ algorithm is widely used in the scientific field and has a significant impact on phase retrieval, medical image reconstruction, signal processing, etc. Moudafi proposed an alternating CQ algorithm to solve the split equality problem, but he only obtained the result of weak convergence. The work of this paper is to improve his algorithm so that the generated iterative sequence can converge strongly.
1. Introduction
Let , be two nonempty closed convex subsets, and are real Hilbert spaces. For all , , the equality is true, is called the adjoint operator of A. The split feasibility problem (SFP) can be described as finding such that
where is a linear bounded operator.
The SFP was first proposed by Censor and Elfving [1]. It is used to model the inverse problems of phase retrieval and medical image reconstruction in finite-dimensional Hilbert spaces. It has a significant impact on signal processing, image reconstruction and radiation therapy, see [2,3,4]. The following CQ algorithm proposed by Byrne [4] is an important method to solve the SFP
where , represents the largest eigenvalue of the operator . Recently, many other algorithms have appeared to solve problem (1), for example, [5,6,7,8].
Let and be nonempty closed convex subsets, and are real Hilbert spaces, and are two non-negative integers. is also a real Hilbert space. The multiple-sets split equality problem (MSSEP) can be described as finding , such that
where and are two linear bounded operators.
Remark 1.
When , the MSSEP is reduced to an MSSFP. The MSSFP is widely used in intensity-modulated radiation therapy (IMRT) [9,10,11,12,13], image reconstruction [14,15,16], signal processing [17,18,19,20,21]. Recently, many other algorithms have appeared to solve the MSSFP, see [22,23,24].
Remark 2.
When , the MSSEP is reduced to a split equality problem (SEP).
The SEP can be described as finding , such that
The SEP is applied to optimal control and approximation theory [25], in intensity-modulated radiation therapy (IMRT) [26] and game theory [27]. Byrne [28] proposed the following Landweber projection algorithm to study the SEP:
Different from Byrne’s algorithm, Moudafi [29] proposed the following alternating CQ algorithm
However, Moudafi only obtained the result of weak convergence. Inspired by this work, we propose an improved alternating CQ algorithm to solve the SEP. This improved method changes the iterative sequence from weak to strong convergence.
The structure of this article is as follows. In Section 2, we review some of the definitions, properties, and lemmas used to prove the convergence of the method. In Section 3, we propose a new algorithm and prove its strong convergence. In Section 4, at the end of the article, we reach a conclusion.
2. Preliminaries
We define the strong convergence of sequence as and weak convergence as , . Let be a nonempty closed convex subset, is a real Hilbert space, , the orthogonal projection from to C is defined by
Definition 1
([30]). Let be a nonempty closed convex subset, is a real Hilbert space, for all , and , we have
- 1.
- ;
- 2.
- ;
- 3.
- .
- 4.
- .
Lemma 1
([31]). For all , is a real Hilbert space, we have
Lemma 2
([32]). For all , assume that the three sequences , , satisfy the following conditions:
- 1.
- ;
- 2.
- and ;
- 3.
- ;
- 4.
- .
Then, the following conclusion holds:
3. Main Results
Let the solution set of problem (4) given by . We propose the following new alternating CQ algorithm to solve problem (4):
Assume that and are two given points, the sequence satisfies , and . Below, we prove the strong convergence of the sequence generated by Equation (7).
Theorem 1.
Proof.
Let , which is, , , . According to (4) of Definition 1 and Lemma 1, on the one hand, we have
It follows that
We consider first
Then, we consider
Then, Equation (9) becomes
On the other hand, we have
It follows that
We have
At the same time, we have
Then, Equation (14) becomes
We have
and
In the light of , combining equalities (18) and (19), adding Equations (12) and (17) together, we finally obtain
It follows that
We assume , in view of (21), we then obtain the following result
According to the conditions of sequence , we deduced
We note that
According to the condition of the sequence , we have
According to Equation (23), we obtain that the sequence is bounded. Therefore, in view of Equation (25), the sequences and are bounded.
Let and be the convergence points of sequences and , respectively. We obtain
It follows that
It follows that
This implies
where
Because and are bounded, we obtain
It follows that . Let , , we assume that , for all , there exists such that . Then, in view of Equation (30), we have
Since , there exists such that . We deduced that
In view of Equation (25), we know that is a non-negative real sequence, the inequality in Equation (34) contradicts the fact, hence, . Since has a finite limit, we take a subsequence such that
We assume that and have finite limits, then the following limit exists
and
Since , we deduce that
and
From Equation (38), we obtain that any weak cluster point of belongs to . Hence, it follows that
and
This implies that any weak cluster point of belongs to . We assume that weakly converges to , then, we have
In the light of Lemma 2, we have . From Equation (25), we obtain
Therefore, we obtain
Then,
Hence, . We obtain that and . This proof has been completed.
Let and be two strict contraction mappings with contraction coefficients of and , respectively.
□
4. Conclusions
In this paper, we proposed an improved alternating CQ algorithm to solve the SEP. This improved method changes the generated iterative sequence from weak to strong convergence.
Author Contributions
Validation, N.-N.T.; Writing—original draft, Y.-J.H.; Writing—review & editing, L.-J.Z. The three authors of this article made equal contributions. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the National Natural Science Foundation of China (210170121), the construction project of first-class subjects in Ningxia higher education (213170023).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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