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Hybrid simultaneous algorithms for the split equality problem with applications
Journal of Inequalities and Applications volume 2016, Article number: 198 (2016)
Abstract
The split equality problem has board applications in many areas of applied mathematics. Many researchers studied this problem and proposed various algorithms to solve it. From the literature we know that most algorithms for the split equality problems came from the idea of the projected Landweber algorithm proposed by Byrne and Moudafi (Working paper UAG, 2013), and few algorithms came from the idea of the alternating CQ-algorithm given by Moudafi (Nonlinear Anal. 79:117-121, 2013). Hence, it is important and necessary to give new algorithms from the idea of the alternating CQ-algorithm. In this paper, we first present a hybrid projected Landweber algorithm to study the split equality problem. Next, we propose a hybrid alternating CQ-algorithm to study the split equality problem. As applications, we consider the split feasibility problem and linear inverse problem. Finally, we give numerical results for the split feasibility problem to demonstrate the efficiency of the proposed algorithms.
1 Introduction
Let H be a real Hilbert space with inner product \(\langle\cdot ,\cdot\rangle\) and norm \(\|\cdot\|\). We denote the strong convergence and weak convergence of \(\{x_{n}\}_{n\in\mathbb{N}}\) to \(x\in H\) by \(x_{n}\to x\) and \(x_{n}\rightharpoonup x\), respectively. The symbols \(\mathbb{N}\) and \(\mathbb{R}\) are used to denote the sets of positive integers and real numbers, respectively. For each \(x\in H\), there is a unique element \(\bar{x}\in C\) such that \(\|x-\bar {x}\|=\min_{y\in C}\|x-y\|\). In this study, we set \(P_{C}x=\bar{x}\), and \(P_{C}\) is called the metric projection from H onto C.
Let \(H_{1}\) and \(H_{2}\) be two real Hilbert spaces. Let \(A:H_{1}\rightarrow H_{2}\) and \(A^{*}:H_{2}\rightarrow H_{1}\) be two linear and bounded operators. Then \(A^{*}\) is called the adjoint of A if \(\langle Az,w\rangle=\langle z,A^{*}w\rangle\) for all \(z\in H_{1}\) and \(w\in H_{2}\). It is known that the adjoint operator of a linear and bounded operator on a Hilbert space always exists and is linear, bounded, and unique. Further, we know that \(\|A\|=\|A^{*}\|\).
Let \(H_{1}\), \(H_{2}\), and \(H_{3}\) be real Hilbert spaces. Let C and Q be nonempty closed convex subsets of \(H_{1}\) and \(H_{2}\), respectively. Let \(A:H_{1}\rightarrow H_{3}\) and \(B:H_{2}\rightarrow H_{3}\) be linear and bounded operators with adjoint operators \(A^{* }\) and \(B^{* }\), respectively. The following problem is the split equality problem, which was studied by Moudafi [2, 3]:
Let \(\Omega:=\{(x,y)\in C\times Q: Ax=By\}\) be the solution set of problem (SEP). Further, we observed that \((x,y)\) is a solution of the split equality problem if and only if
for all \(\rho_{1}>0\) and \(\rho_{2}>0\) (for details, see [4]).
As mentioned by Moudafi [2], the interest of the split equality problem covers many situations, for instance, in decomposition methods for PDEs, game theory, and intensity modulated radiation therapy (IMRT). For details, see [2, 5, 6]. To solve problem (SEP), Moudafi [3] proposed the alternating CQ-algorithm:
where \(H_{1}=\mathbb{R}^{N}\), \(H_{2}=\mathbb{R}^{M}\), \(P_{C}\) is the metric projection mapping from \(H_{1}\) onto C, and \(P_{Q}\) is the metric projection mapping from \(H_{2}\) onto Q, \(\varepsilon>0\), A is a \(J\times N\) matrix, B is a \(J\times M\) matrix, \(\lambda_{A}\) and \(\lambda_{B}\) are the spectral radii of \(A^{* }A\) and \(B^{* }B\), respectively, and \(\{\rho_{n}\}\) is a sequence in \(( \varepsilon,\min \{ \frac{1}{\lambda_{A}},\frac {1}{\lambda_{B}} \} -\varepsilon ) \).
In 2013, Byrne and Moudafi [1] presented a simultaneous algorithm, which was called the projected Landweber algorithm, to study the split equality problem
where \(H_{1}=\mathbb{R}^{N}\), \(H_{2}=\mathbb{R}^{M}\), \(P_{C}\) is the metric projection mapping from \(H_{1}\) onto C, and \(P_{Q}\) is the metric projection mapping from \(H_{2}\) onto Q, \(\varepsilon>0\), A is a \(J\times N\) matrix, B is a \(J\times M\) matrix, \(\lambda_{A}\) and \(\lambda_{B}\) are the spectral radii of \(A^{* }A\) and \(B^{* }B\), respectively, and \(\{\rho_{n}\}\) is a sequence in \(( \varepsilon, \frac{2}{\lambda_{A}+\lambda_{B}} ) \).
Besides, we also observed that Chen et al. [7] gave the following modification of (ACQA) by using the Tikhonov regularization method and proved a convergence theorem under suitable conditions:
where \(\{\varepsilon_{n}\}_{n\in\mathbb{N}}\) is a sequence in \((0,\infty)\). Besides, many researchers studied problem (SEP) and gave various algorithms. For more details about the algorithms for the split equality problem, we refer to [8, 9] and related references.
Besides, from the literature we know that most algorithms in the literature come from the idea of the projected Landweber algorithm, and few algorithms come from the idea of the alternating CQ-algorithm. Hence, it is important and necessary to give new algorithms from the idea of the alternating CQ-algorithm. In this paper, motivated by the works mentioned on the split equality problem, we present a hybrid projected Landweber algorithm and a hybrid alternating CQ-algorithm to study the split equality problem and give convergence theorems for the proposed algorithms. As applications, we consider the split feasibility problem and linear inverse problem in real Hilbert spaces. Finally, we give numerical results for the split feasibility problem to demonstrate the efficiency of the proposed algorithms.
2 Main results
In the sequel, we need the following lemma, which is a crucial tool for our results.
Lemma 2.1
[10]
Let C be a nonempty closed convex subset of a real Hilbert space H, and let \(P_{C}\) be the metric projection from H onto C. Then:
-
(i)
\(\langle x-P_{C}x,P_{C}x-y\rangle\geq0\) for all \(x\in H\) and \(y\in C\);
-
(ii)
\(\|x-P_{C}x\|^{2}+\|P_{C}x-y\|^{2}\leq\|x-y\|^{2}\) for all \(x\in H\) and \(y\in C\);
-
(iii)
\(\|P_{C}x-P_{C}y\|^{2}\leq\langle x-y,P_{C}x-P_{C}y\rangle\) for all \(x,y\in H\).
2.1 Hybrid projected Landweber algorithm
Let \(H_{1}\), \(H_{2}\), and \(H_{3}\) be real Hilbert spaces with inner product \(\langle\cdot,\cdot\rangle_{H_{i}}\) and norm \(\|\cdot \|_{H_{i}}\), \(i=1,2,3\). For simplicity, we write \(\langle\cdot,\cdot\rangle\) and \(\|\cdot\|\). Let C and Q be nonempty closed convex subsets of \(H_{1}\) and \(H_{2}\), respectively. Let \(A:H_{1}\rightarrow H_{3}\) and \(B:H_{2}\rightarrow H_{3}\) be linear and bounded operators with adjoint operators \(A^{* }\) and \(B^{* }\), respectively. Choose \(\delta\in(0,1)\). Let Ω be the solution set of the split equality problem and suppose that \(\Omega\neq\emptyset\). Let \(\{\rho_{n}\}_{n\in\mathbb{N}}\) be a sequence in \((0,\infty)\).
Now we present a hybrid projected Landweber algorithm to study the split equality problem.
Algorithm 2.1
For given \(x_{n}\in H_{1}\) and \(y_{n}\in H_{2}\), find the approximate solution by the following iterative process.
- Step 1.:
-
Compute the next iterate \((u_{n},v_{n})\) as follows:
$$ \left \{ \textstyle\begin{array}{l} u_{n}=P_{C}[x_{n}-\rho_{n}A^{*}(Ax_{n}-By_{n})], \\ v_{n}=P_{Q}[y_{n}+\rho_{n}B^{*}(Ax_{n}-By_{n})],\end{array}\displaystyle \right . $$where \(\rho_{n}>0\) satisfies
$$\begin{aligned}& \rho _{n}^{2}\bigl(\bigl\Vert A^{*}(Ax_{n}-By_{n})-A^{*}(Au_{n}-Bv_{n}) \bigr\Vert ^{2}+\bigl\Vert B^{*}(Ax_{n}-By_{n})-B^{*}(Au_{n}-Bv_{n}) \bigr\Vert ^{2}\bigr) \\& \quad \leq \delta \Vert x_{n}-u_{n}\Vert ^{2}+\delta \Vert y_{n}-v_{n}\Vert ^{2}, \quad 0< \delta< 1. \end{aligned}$$(2.1) - Step 2.:
-
If \(x_{n}=u_{n}\) and \(y_{n}=v_{n}\), then \((x_{n},y_{n})\) is a solution of problem (SEP) and stop. Otherwise, go to Step 3.
- Step 3.:
-
Compute the next iterate \((x_{n+1},y_{n+1})\) as follows:
$$ \left \{ \textstyle\begin{array}{l} D_{(n,1)}:=x_{n}-u_{n}+\rho_{n}[A^{*}(Au_{n}-Bv_{n})-A^{*}(Ax_{n}-By_{n})], \\ D_{(n,2)}:=y_{n}-v_{n}-\rho_{n}[B^{*}(Au_{n}-Bv_{n})-B^{*}(Ax_{n}-By_{n})], \\ \alpha_{n}:=\frac{\langle x_{n}-u_{n},D_{(n,1)}\rangle+\langle y_{n}-v_{n},D_{(n,2)}\rangle}{\|D_{(n,1)}\|^{2}+\|D_{(n,2)}\|^{2}}, \\ x_{n+1}=P_{C}[x_{n}-\alpha_{n} D_{(n,1)}], \\ y_{n+1}=P_{Q}[y_{n}-\alpha_{n} D_{(n,2)}]. \end{array}\displaystyle \right . $$Next, update \(n:=n+1\) and go to Step 1.
Remark 2.1
If \(0<\rho_{n}\leq\frac{\sqrt{\delta}}{\sqrt {2}(\|A\|^{2}+\|B\|^{2})}\), then (2.1) holds.
Proof
Without loss of generality, we may assume that \(x_{n}\neq u_{n}\) and \(y_{n}\neq v_{n}\). We know that
Therefore, the proof is completed. □
Theorem 2.1
Let \(\{\rho_{n}\}_{n\in\mathbb{N}}\) be a sequence in \((0,2/(\|A\|^{2}+\|B\|^{2}))\) such that (2.1) holds and assume that \(\liminf_{n\rightarrow\infty}\rho_{n}(2-\rho_{n}(\|A\|^{2}+\|B\|^{2}))>0\). Then, for the sequence \(\{(x_{n},y_{n})\}_{n\in\mathbb{N}}\) in Algorithm 2.1, there exists \((\bar{x},\bar{y})\in\Omega\) such that \(x_{n}\rightharpoonup\bar {x}\) and \(y_{n}\rightharpoonup\bar{y}\) as \(n\rightarrow\infty\).
Proof
Take any \(n\in\mathbb{N}\) and let n be fixed. Take any \((\bar{u},\bar{v})\in\Omega\) and let \((\bar{u},\bar{v})\) be fixed. Then \(\bar{u}\in C\), \(\bar{v}\in Q\), and \(A\bar{u}=B\bar{v}\). First, we set
Then
By (2.2) we know that
Next, by Lemma 2.1 we know that
and
Hence, by (2.4),
Similarly, we have
Next, we know that
By Lemma 2.1,
and
Besides, we also have
So, by (2.9), (2.10), (2.11), and (2.12) we determine that
which implies that
So, \(\{\|x_{n}-\bar{u}\|^{2}+\|y_{n}-\bar{v}\|^{2}\}\) is a decreasing sequence, and \(\lim_{n\rightarrow\infty}\|x_{n}-\bar{u}\|^{2}+\|y_{n}-\bar{v}\|^{2}\) exists. Further, \(\{x_{n}\}_{n\in\mathbb{N}}\) and \(\{y_{n}\}_{n\in \mathbb{N}}\) are bounded sequences, and
Besides, we know that
which implies that
Hence, by (2.18) we derive that
By (2.16) and (2.19) we know that
By Lemma 2.1 again,
Similarly,
We also have
By (2.20), (2.23), and (2.24) we get
Since \(\{x_{n}\}_{n\in\mathbb{N}}\) and \(\{y_{n}\}_{n\in\mathbb{N}}\) are bounded sequences, there exist subsequences \(\{x_{n_{k}}\}_{k\in\mathbb{N}}\) and \(\{y_{n_{k}}\}_{k\in\mathbb{N}}\) of \(\{x_{n}\}_{n\in\mathbb{N}}\) and \(\{y_{n}\}_{n\in\mathbb{N}}\), respectively, such that \(x_{n_{k}}\rightharpoonup\bar{x}\) and \(y_{n_{k}}\rightharpoonup\bar{y}\) for some \(\bar{x}\in H_{1}\) and \(\bar{y}\in H_{2}\). Since \(\{x_{n}\} _{n=2}^{\infty}\) is a sequence in C, we know that \(\bar{x}\in C\). Also, \(\bar{y}\in Q\). Since \(x_{n_{k}}\rightharpoonup\bar{x}\) and \(y_{n_{k}}\rightharpoonup\bar{y}\), it is easy to see that \(Ax_{n_{k}}\rightharpoonup A\bar{x}\) and \(By_{n_{k}}\rightharpoonup B\bar {y}\) by using the properties of A and B. Further, \(Ax_{n_{k}}-By_{n_{k}}\rightharpoonup A\bar{x}-B\bar{y}\), and the lower semicontinuity of the squared norm implies
Then \(A\bar{x}=B\bar{y}\) and \((\bar{x},\bar{y})\in\Omega\).
Next, let \(\{x^{\prime}_{n_{k}}\}\) and \(\{y^{\prime}_{n_{k}}\}\) be other subsequences of \(\{x_{n}\}_{n\in\mathbb{N}}\) and \(\{y_{n}\}_{n\in \mathbb{N}}\) such that \(x^{\prime}_{n_{k}}\rightharpoonup\hat{x}\) and \(y^{\prime}_{n_{k}}\rightharpoonup\hat{y}\), respectively. Following the same argument as before, we get that \((\hat{x},\hat{y})\in\Omega \). Besides, we have
and
Clearly, \(\lim_{n\rightarrow\infty}\|x_{n}-\bar {x}\|^{2}+\|y_{n}-\bar{y}\|^{2}\) exists, and \(\lim_{n\rightarrow\infty}\|x_{n}-\hat {x}\|^{2}+\|y_{n}-\hat{y}\|^{2}\) exists. Hence, by (2.27) we get
Similarly, by (2.28) we have
By (2.29) and (2.30) we know that \(\bar{x}=\hat{x}\) and \(\bar{y}=\hat{y}\). Therefore, \(x_{n}\rightharpoonup\bar{x}\) and \(y_{n}\rightharpoonup\bar{y}\), and the proof is completed. □
Remark 2.2
In Theorem 2.1, if we choose \(\{\rho_{n}\} _{n\in\mathbb{N}}\) from \(( 0,\frac{\delta}{\sqrt {2}(\|A\|^{2}+\|B\|^{2})} ]\), then we only need to assume that \(\liminf_{n\rightarrow\infty}\rho _{n}>0\).
Proof
Since \(\rho_{n}\in ( 0,\frac{\delta }{\sqrt{2}(\|A\|^{2}+\|B\|^{2})} ]\), we have
which implies that
Since \(\liminf_{n\rightarrow\infty}\rho_{n}>0\), we may assume that there is κ such that \(\rho_{n}\geq\kappa>0\) for all \(n\in \mathbb{N}\). Hence, we determine
By (2.33) we get the conclusion of Remark 2.2. □
2.2 Hybrid alternating CQ-algorithm
In this subsection, we present a hybrid alternating CQ-algorithm to study the split equality problem.
Algorithm 2.2
For given \(x_{n}\in H_{1}\) and \(y_{n}\in H_{2}\), find the approximate solution by the following iterative process.
- Step 1.:
-
Compute the next iterate \((u_{n},v_{n})\) as follows:
$$ \left \{ \textstyle\begin{array}{l} u_{n}=P_{C}[x_{n}-\rho_{n}A^{*}(Ax_{n}-By_{n})], \\ v_{n}=P_{Q}[y_{n}+\rho_{n}B^{*}(Au_{n}-By_{n})],\end{array}\displaystyle \right . $$where \(\rho_{n}>0\) satisfies
$$\begin{aligned}& \rho _{n}^{2}\bigl(\bigl\Vert A^{*}(Ax_{n}-By_{n})-A^{*}(Au_{n}-Bv_{n}) \bigr\Vert ^{2}+\bigl\Vert B^{*}(Au_{n}-By_{n})-B^{*}(Au_{n}-Bv_{n}) \bigr\Vert ^{2}\bigr) \\& \quad \leq \delta \Vert x_{n}-u_{n}\Vert ^{2}+\delta \Vert y_{n}-v_{n}\Vert ^{2}, \quad 0< \delta< 1. \end{aligned}$$(2.34) - Step 2.:
-
If \(x_{n}=u_{n}\) and \(y_{n}=v_{n}\), then \((x_{n},y_{n})\) is a solution of problem (SEP) and stop. Otherwise, go to Step 3.
- Step 3.:
-
Compute the next iterate \((x_{n+1},y_{n+1})\) as follows:
$$ \left \{ \textstyle\begin{array}{l} D_{(n,1)}:=x_{n}-u_{n}+\rho_{n}[A^{*}(Au_{n}-Bv_{n})-A^{*}(Ax_{n}-By_{n})], \\ D_{(n,2)}:=y_{n}-v_{n}-\rho_{n}[B^{*}(Au_{n}-Bv_{n})-B^{*}(Au_{n}-By_{n})], \\ \alpha_{n}:=\frac{\langle x_{n}-u_{n},D_{(n,1)}\rangle+\langle y_{n}-v_{n},D_{(n,2)}\rangle}{\|D_{(n,1)}\|^{2}+\|D_{(n,2)}\|^{2}}, \\ x_{n+1}=P_{C}[x_{n}-\alpha_{n} D_{(n,1)}], \\ y_{n+1}=P_{Q}[y_{n}-\alpha_{n} D_{(n,2)}]. \end{array}\displaystyle \right . $$Next, update \(n:=n+1\) and go to Step 1.
Remark 2.3
If \(0<\rho_{n}\leq{\frac{\sqrt{\delta}}{\max\{\sqrt{2}\cdot \|A\|^{2},\sqrt{2\cdot\|A\|^{2}\cdot|B\|^{2}+\|B\|^{3}}\}}}\), then (2.34) holds.
Proof
Without loss of generality, we may assume that \(x_{n}\neq u_{n}\) and \(y_{n}\neq v_{n}\). We have
Therefore, the proof is completed. □
Theorem 2.2
Let \(\{\rho_{n}\}_{n\in\mathbb{N}}\) be a sequence in \((0,1/\max \{\|A\|^{2},\|B\|^{2}\})\) such that (2.34) holds and assume that \({\liminf_{n\rightarrow\infty}}\rho_{n}(1-\rho _{n}\|A\|^{2})>0\) or \({\liminf_{n\rightarrow\infty}}\rho_{n}(1-\rho _{n}\|B\|^{2})>0\). Then, for the sequence \(\{(x_{n},y_{n})\}_{n\in\mathbb{N}}\) in Algorithm 2.2, there exists \((\bar{x},\bar{y})\in\Omega\) such that \(x_{n}\rightharpoonup\bar{x}\) and \(y_{n}\rightharpoonup\bar{y}\) as \(n\rightarrow\infty\).
Proof
Take any \(n\in\mathbb{N}\) and let n be fixed. Take any \((\bar{u},\bar{v})\in\Omega\) and let \((\bar{u},\bar{v})\) be fixed. Then \(\bar{u}\in C\), \(\bar{v}\in Q\), and \(A\bar{u}=B\bar{v}\). First, we set
Then
By (2.35) we have that
Next, by Lemma 2.1 we have
and
Hence, by (2.37),
Also, by (2.38),
Next, we have
By Lemma 2.1,
and
Besides, we also have
So, by (2.42), (2.43), (2.44), and (2.45) we determine that
which implies that
By (2.35), (2.41), and (2.47),
So, \(\{\|x_{n}-\bar{u}\|^{2}+\|y_{n}-\bar{v}\|^{2}\}\) is a decreasing sequence, \(\lim_{n\rightarrow\infty}\|x_{n}-\bar {u}\|^{2}+\|y_{n}-\bar{v}\|^{2}\) exists, \(\{x_{n}\}_{n\in\mathbb{N}}\) and \(\{y_{n}\}_{n\in\mathbb{N}}\) are bounded sequences, and
Besides, we have
which implies that
Hence, by (2.51) we derive that
By (2.49) and (2.52) we get that
By Lemma 2.1 again,
Similarly,
We also have
and
By (2.54), (2.55), (2.56), and (2.57),
We also have
Case 1: \(\liminf_{n\rightarrow\infty}\rho_{n}(1-\rho_{n}\|A\|^{2})>0\).
By (2.53), (2.58), and (2.59) we get
Case 2: Suppose that \(\liminf_{n\rightarrow\infty}\rho_{n}(1-\rho_{n}\|B\|^{2})>0 \).
By (2.53), (2.58), and (2.59) we get
By (2.53) and (2.61) we determine
Next, following the same argument as the final proof of Theorem 2.1, we get the conclusion of Theorem 2.2. □
Remark 2.4
Suppose that \(\{\rho_{n}\}_{n\in\mathbb{N}}\) satisfy the following inequality:
Then \(\{\rho_{n}\}_{n\in\mathbb{N}}\) satisfy the conditions in Remark 2.3 and Theorem 2.2.
3 Applications of the split equality problem
3.1 The split feasibility problem
Let \(H_{1}\) and \(H_{2}\) be real Hilbert spaces. Let C and Q be nonempty closed convex subsets of \(H_{1}\) and \(H_{2}\), respectively. Let \(A:H_{1}\rightarrow H_{2}\) be a linear and bounded operator with adjoint operator \(A^{* }\). The following problem is the split feasibility problem in Hilbert spaces, which was first introduced by Censor and Elfving [11]:
Here, let \(\Omega_{1}:=\{x\in C: Ax\in Q\}\) be the solution set of problem (SFP). It is worth noting that this problem is a particular case of the split equality problem when \(H_{3}=H_{2}\) and B is the identity mapping on \(H_{2}\). For additional details, one can refer to [6, 11–24] and related literature.
By Algorithm 2.2, we get the following algorithm to study problem (SFP).
Algorithm 3.1
For given \(x_{n}\in H_{1}\) and \(y_{n}\in H_{2}\), find the approximate solution by the following iterative process.
- Step 1.:
-
For \(n\in\mathbb{N}\), let \(u_{n}\) and \(v_{n}\) be defined by
$$ \left \{ \textstyle\begin{array}{l} u_{n}=P_{C}[x_{n}-\rho_{n}A^{*}(Ax_{n}-y_{n})], \\ v_{n}=P_{Q}[y_{n}+\rho_{n}(Au_{n}-y_{n})],\end{array}\displaystyle \right . $$where \(\rho_{n}>0\) satisfies
$$\begin{aligned}& \rho_{n}^{2}\bigl(\bigl\Vert A^{*}(Ax_{n}-y_{n})-A^{*}(Au_{n}-v_{n}) \bigr\Vert ^{2}+\bigl\Vert (Au_{n}-y_{n})-B^{*}(Au_{n}-v_{n}) \bigr\Vert ^{2}\bigr) \\& \quad \leq \delta \Vert x_{n}-u_{n}\Vert ^{2}+\delta \Vert y_{n}-v_{n}\Vert ^{2},\quad 0< \delta< 1. \end{aligned}$$(3.1) - Step 2.:
-
If \(x_{n}=u_{n}\) and \(y_{n}=v_{n}\), then \((x_{n},y_{n})\) is a solution of problem (SFP) and stop. Otherwise, go to Step 3.
- Step 3.:
-
Compute the next iterate \((x_{n+1},y_{n+1})\) as follows:
$$ \left \{ \textstyle\begin{array}{l} D_{(n,1)}:=x_{n}-u_{n}+\rho_{n}[A^{*}(Au_{n}-v_{n})-A^{*}(Ax_{n}-y_{n})], \\ D_{(n,2)}:=y_{n}-v_{n}-\rho_{n}[(Au_{n}-v_{n})-(Au_{n}-y_{n})], \\ \alpha_{n}:=\frac{\langle x_{n}-u_{n},D_{(n,1)}\rangle+\langle y_{n}-v_{n},D_{(n,2)}\rangle}{\|D_{(n,1)}\|^{2}+\|D_{(n,2)}\|^{2}}, \\ x_{n+1}=P_{C}[x_{n}-\alpha_{n} D_{(n,1)}], \\ y_{n+1}=P_{Q}[y_{n}-\alpha_{n} D_{(n,2)}].\end{array}\displaystyle \right . $$Next, update \(n:=n+1\) and go to Step 1.
We get the following convergence theorem for the split feasibility problem by using Theorem 2.2.
Theorem 3.1
Let \(H_{1}\) and \(H_{2}\) be real Hilbert spaces. Let C and Q be nonempty closed convex subsets of \(H_{1}\) and \(H_{2}\), respectively. Let \(A:H_{1}\rightarrow H_{2}\) be a linear and bounded operator with adjoint operator \(A^{* }\). Choose \(\delta\in(0,1)\). Let \(\Omega_{1}\) be the solution set of the split feasibility problem and suppose that \(\Omega_{1}\neq\emptyset\). Let \(\{\rho _{n}\}_{n\in\mathbb{N}}\) be a sequence in \((0,1/\max\{\|A\|^{2},1\} )\) such that (3.1) hold and assume that \({\liminf_{n\rightarrow\infty}}\rho_{n}(1-\rho _{n}\|A\|^{2})>0\) or \({\liminf_{n\rightarrow\infty}}\rho_{n}(1-\rho_{n})>0\) s. Then, for the sequence \(\{(x_{n},y_{n})\}_{n\in\mathbb{N}}\) in Algorithm 3.1, there exists \(\bar{x}\in\Omega_{1}\) such that \(x_{n}\rightharpoonup\bar {x}\) as \(n\rightarrow\infty\).
3.2 Linear inverse problem
In this subsection, we study an inverse problem by our algorithms and convergence theorems. Let \(H_{1}\) and \(H_{2}\) be real Hilbert spaces. Let C be a nonempty closed convex subset of \(H_{1}\), and \(A:H_{1}\rightarrow H_{2}\) be a linear and bounded operator with adjoint operator \(A^{*}\). Given \(b\in H_{2}\). Then we consider the following inverse problem in this section:
This is a particular case of the split equality problem if \(H_{2}=H_{3}\), \(Q=\{b\}\), and \(B(x)=x\) for all \(x\in H_{2}\). Next, take any \((x_{1},y_{1})\in H_{1}\times H_{2} \) with \(y_{1}=b\). Then, by Algorithm 2.2 we get the following algorithm to study problem (IV).
Algorithm 3.2
For given\(x_{n}\in H_{1}\), find the approximate solution by the following iterative process.
- Step 1.:
-
Compute the next iterate \(u_{n}\) as follows:
$$ u_{n}=P_{C}\bigl[x_{n}-\rho_{n}A^{*}(Ax_{n}-b) \bigr], $$where \(\rho_{n}>0\) satisfies
$$ \rho_{n}^{2}\cdot\bigl\Vert A^{*}(Ax_{n})-A^{*}(Au_{n})\bigr\Vert ^{2}\leq \delta \Vert x_{n}-u_{n}\Vert ^{2},\quad 0< \delta< 1. $$(3.2) - Step 2.:
-
If \(x_{n}=u_{n}\), then \(x_{n}\) is a solution of problem (IV) and stop. Otherwise, go to Step 3.
- Step 3.:
-
Compute the next iterate \(x_{n+1}\) as follows:
$$ \left \{ \textstyle\begin{array}{l} D_{n}:=x_{n}-u_{n}+\rho_{n}[A^{*}(Au_{n})-A^{*}(Ax_{n})], \\ \alpha_{n}:=\frac{\langle x_{n}-u_{n},D_{n}\rangle}{\|D_{n}\|^{2}}, \\ x_{n+1}=P_{C}[x_{n}-\alpha_{n} D_{n}].\end{array}\displaystyle \right . $$Next, update \(n:=n+1\) and go to Step 1.
We get the following convergence theorem for the linear inverse problem by using Theorem 2.2.
Theorem 3.2
Let \(H_{1}\) and \(H_{2}\) be real Hilbert spaces. Let C be a nonempty closed convex subset of \(H_{1}\), and \(A:H_{1}\rightarrow H_{2}\) be a linear and bounded operator with adjoint operator \(A^{* }\). Given \(b\in H_{2}\) and \(\delta \in(0,1)\). Let \(\Omega_{2}\) be the solution set of (IV) and suppose that \(\Omega _{2}\neq\emptyset\). Let \(\{\rho_{n}\}_{n\in\mathbb{N}}\) be a sequence in \((0,1/\max\{\|A\|^{2},1\})\) such that (3.2) holds and assume that \({\liminf_{n\rightarrow\infty}}\rho _{n}(1-\rho_{n}\|A\|^{2})>0\) or \({\liminf_{n\rightarrow\infty}}\rho _{n}(1-\rho_{n})>0\). Then, for the sequence \(\{x_{n}\}_{n\in\mathbb {N}}\) in Algorithm 3.2, there exists \(\bar{x}\in\Omega_{2}\) such that \(x_{n}\rightharpoonup \bar{x}\) as \(n\rightarrow \infty\).
Remark 3.1
By Algorithm 2.1 and Theorem 2.1, we can get the related algorithms and convergence theorems for the split feasibility problem and the inverse problems.
4 Numerical results
All codes were written in R language (version 3.2.4 (2016-03-10), the R Foundation for Statistical Computing Platform: x86-64-w64-mingw32/x64).
Example 4.1
Let \(H_{1}=H_{2}=H_{3}=\mathbb{R}^{2}\), \(C:=\{x\in\mathbb{R}^{2}: \|x\|\leq1\} \), \(Q:=\{x=(u,v)\in\mathbb{R}^{2}: (u-6)^{2}+(v-8)^{2}\leq25\}\),
Then problem (SEP) has a unique solution \((\bar{x},\bar{y})\in \mathbb{R}^{2}\times\mathbb{R}^{2}\), where \(\bar{x}:=(\bar{x}_{1},\bar {x}_{2})\), \(\bar{y}:=(\bar{y}_{1},\bar{y}_{2})\). Indeed, \(\bar{x}_{1}=0.6\), \(\bar{x}_{2}=0.8\), \(\bar{y}_{1}=3\), \(\bar{y}_{2}=4\). Let \(\varepsilon>0\) and the algorithm stop if \(\|x_{n}-\bar{x}\|+\|y_{n}-\bar {y}\|<\varepsilon\).
In Table 1, setting \(\varepsilon=10^{-1}\), \(x_{1}=(10,10)^{T}\), \(y_{1}=(1,1)^{T}\), and \(\rho_{n}=0.01\) for all \(n\in\mathbb{N}\), we get the numerical results.
In Table 2, setting \(\varepsilon=10^{-1}\), \(x_{1}=(5,5)^{T}\), \(y_{1}=(1,1)^{T}\), and \(\rho_{n}=0.01\) for all \(n\in\mathbb{N}\), we get the numerical results.
In Table 3, setting \(\varepsilon=4\times10^{-2}\), \(x_{1}=(-12,-50)^{T}\), \(y_{1}=(-40,20)^{T}\), and \(\rho_{n}=0.01\) for all \(n\in\mathbb{N}\), we get the numerical results.
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Acknowledgements
Prof. Wei-Shih Du was supported by Grant No. MOST 104-2115-M-017-002 of the Ministry of Science and Technology of the Republic of China.
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Chuang, CS., Du, WS. Hybrid simultaneous algorithms for the split equality problem with applications. J Inequal Appl 2016, 198 (2016). https://doi.org/10.1186/s13660-016-1141-x
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DOI: https://doi.org/10.1186/s13660-016-1141-x