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Nonlinear algorithms approach to split common solution problems

Abstract

In this paper, we introduce some new iterative algorithms for the split common solution problems for equilibrium problems and fixed point problems of nonlinear mappings. Some examples illustrating our results are also given.

MSC:47J25, 47H09, 65K10.

1 Introduction

Throughout this paper, we assume that H is a real Hilbert space with zero vector θ, whose inner product and norm are denoted by , and , respectively. Let K be a nonempty subset of H and T be a mapping from K into itself. The set of fixed points of T is denoted by F(T). The symbols and are used to denote the sets of positive integers and real numbers, respectively.

Let C and K be nonempty subsets of real Banach spaces E 1 and E 2 , respectively. Let A: E 1 E 2 be a bounded linear mapping, T a mapping from C into itself with F(T) and f a bi-function from K×K into R. The classical equilibrium problem is to find xK such that

f(x,y)0,yK.
(1.1)

The symbol EP(f) is used to denote the set of all solutions of the problem (1.1), that is,

EP(f)= { u K : f ( u , v ) 0 , v K } .

The equilibrium problem contains optimization problems, variational inequalities problems, saddle point problems, the Nash equilibrium problems, fixed point problems, complementary problems, bilevel problems, and semi-infinite problems as special cases and have many applications in mathematical program with equilibrium constraint; for detail, one can refer to [14] and references therein.

In this paper, we study the following split common solution problem (SCSP) for equilibrium problems and fixed point problems of nonlinear mappings A, T and f:

(SCSP) Find pC such that pF(T) and u:=ApK which satisfies f(u,v)0, vK. The solution set of (SCSP) is denoted by

Γ= { p F ( T ) : A p EP ( f ) } .

Many authors had proposed some methods to find the solution of the equilibrium problem (1.1). As a generalization of the equilibrium problem (1.1), finding a common solution for some equilibrium problems and fixed point problems of nonlinear operators, it has been considered in the same subset of the same space; see [515]. However, some equilibrium problems and fixed point problems of nonlinear mappings always belong to different subsets of spaces in general. So the split common solution is very important for the research on generalized equilibriums problems and fixed point problems.

Example 1.1 Let E 1 = E 2 =R, C:=[1,+) and K:=(,2]. Let A(x)=2x for all xR and Tx= 2 x x + 1 for all xC. Let f:K×KR be define by f(u,v)=2(uv) for all u,vK. Clearly, A is a bounded linear operator, F(T)={1} and A(1)=2EP(f). So Γ={pF(T):ApEP(f)}.

Example 1.2 Let E 1 = R 2 with the norm α= ( a 1 2 + a 2 2 ) 1 2 for α=( a 1 , a 2 ) R 2 and E 2 =R with the standard norm ||. Let C:={α=( a 1 , a 2 ) R 2 | a 1 2 + a 2 2 1} and K:=[2,2]. Let Aα=2 a 1 for α=( a 1 , a 2 ) E 1 and Tα=( a 1 2 , a 2 2 ) for all α=( a 1 , a 2 )C. Then F(T)={(0,1),(1,0),(0,0)} and A is a bounded and linear operator from E 1 into E 2 with A=2. Now define a bi-function f as f(u,v)=vu for all u,vK. Then f is a bi-function from K×K into with EP(f)={2}.

Clearly, p=(1,0)F(T), Ap=2EP(f). So Γ={pF(T):ApEP(f)}.

Remark 1.1 It is worth to mention that the split common solution problem in Example 1.1 lies in two different subsets of the same space and the split common solution problem in Example 1.2 lies in two different subsets of the different space. So, Examples 1.1 and 1.2 also show that the split common solution problem is meaningful.

In this paper, we introduce a weak convergence algorithm and a strong convergence algorithm for the split common solution problem when the nonlinear operator T is a quasi-nonexpansive mapping. Some strong and weak convergence theorems are established. We also give some examples to illustrate our results.

2 Preliminaries

We write x n x to indicate that the sequence { x n } weakly converges to x and x n x will symbolize strong convergence as usual.

A Banach space (X,) is said to satisfy Opial’s condition, if for each sequence { x n } in X which converges weakly to a point xX, we have

lim inf n x n x< lim inf n x n y,yX,yx.

It is well known that any Hilbert space satisfies Opial’s condition.

Let K be a nonempty subset of real Hilbert spaces H. Recall that a mapping T:KK is said to be nonexpansive if TxTyxy for all x,yK and quasi-nonexpansive if F(T) and TxTpxp for all xK, pF(T).

Example 2.1 Let H=R with the inner product defined by x,y=xy for all x,yR and the standard norm ||. Let C:=[0,+) and Tx= x 2 + 2 1 + x for all xC. Obviously, F(T)={2}. It is easy to see that

|Tx2|= x 1 + x |x2||x2|for xC

and

|T(0)T ( 1 3 ) |= 5 12 >|0 1 3 |.

Hence, T is a continuous quasi-nonexpansive mapping but not nonexpansive.

Definition 2.1 (see [16])

Let K be a nonempty closed convex subset of a real Hilbert space H and T a mapping from K into K. The mapping T is said to be demiclosed if, for any sequence { x n } which weakly converges to y, and if the sequence {T x n } strongly converges to z, then Ty=z.

Remark 2.1 In Definition 2.1, the particular case of demiclosedness at zero is frequently used in some iterative convergence algorithms, which is the particular case when z=θ, the zero vector of H; for more detail, one can refer to [16].

The following concept of zero-demiclosedness was introduced in [17].

Definition 2.2 (see [17])

Let K be a nonempty, closed, and convex subset of a real Hilbert space and T a mapping from K into K. The mapping T is called zero-demiclosed if { x n } in K satisfying x n T x n 0 and x n zK implies Tz=z.

The following result was essentially proved in [17], but we give the proof for the sake of completeness.

Proposition 2.1 Let K be a nonempty, closed, and convex subset of a real Hilbert space with zero vector θ and T a mapping from K into K. Then the following statements hold.

  1. (a)

    T is zero-demiclosed if and only if IT is demiclosed at θ;

  2. (b)

    If T is a nonexpansive mappings and there is a bounded sequence { x n }H such that x n T x n 0 as n0, then T is zero-demiclosed.

Proof Obviously, the conclusion (a) holds. To see (b), since { x n } is bounded, there is a subsequence { x n k }{ x n } and zH such that x n k z. One can claim Tz=z. Indeed, if Tzz, it follows from the Opial’s condition that

lim inf k x n k z < lim inf k x n k T z lim inf k { x n k T x n k + T x n k T z } = lim inf k T x n k T z lim inf k x n k z ,

which is a contradiction. So Tz=z and hence T is zero-demiclosed. □

Example 2.2 Let H, C, and T be the same as in Example 2.1. Let { x n } be a sequence in C. If x n z and x n T x n 0, then zF(T)={2}. Indeed, since T is continuous, we have Tz=z and zF(T)={2}. Hence, T is zero-demiclosed.

Example 2.3 Let H=R with the inner product defined by x,y=xy for all x,yR and the standard norm ||. Let C:=[0,+). Let T be a mapping from C into C defined by

Tx={ 2 x x 2 + 1 , x ( 1 , + ) , 0 , x [ 0 , 1 ] .

Then T is a discontinuous quasi-nonexpansive mapping but not zero-demiclosed.

Proof Obviously, F(T)={0}, and T is a quasi-nonexpansive operator. On the other hand, let x n =1+ 1 n for all nN, then it is not hard to prove that x n 1, x n T x n 0 and 1F(T). So T is not zero-demiclosed. □

Let H 1 and H 2 be two Hilbert spaces. Let A: H 1 H 2 and B: H 2 H 1 be two bounded linear operators. B is called the adjoint operator (or adjoint) of A, if for all z H 1 , w H 2 , B satisfies Az,w=z,Bw. It is known that the adjoint operator of a bounded linear operator on a Hilbert space always exists and is bounded linear and unique. Moreover, it is not hard to show that if B is an adjoint operator of A, then A=B.

Example 2.4 Let H 1 = R 3 with the norm α= ( a 1 2 + a 2 2 + a 3 2 ) 1 2 for α=( a 1 , a 2 , a 3 ) R 2 and H 2 = R 4 with the norm γ= ( c 1 2 + c 2 2 + c 3 2 + c 4 2 ) 1 2 for γ=( c 1 , c 2 , c 3 , c 4 ) R 4 . Let α,β= a 1 b 1 + a 2 b 2 + a 3 b 3 and γ,η= c 1 d 1 + c 2 d 2 + c 3 d 3 + c 4 d 4 denote the inner product of H 1 and H 2 , respectively, where α=( a 1 , a 2 , a 3 ), β=( b 1 , b 2 , b 3 ) H 1 , γ=( c 1 , c 2 , c 3 , c 4 ), η=( d 1 , d 2 , d 3 , d 4 ) H 2 . Let Aα=( a 3 , a 1 + a 2 , a 1 a 2 , a 3 ) for α=( a 1 , a 2 , a 3 ) H 1 . Then A is a bounded linear operator from H 1 into H 2 with A= 2 . For γ=( c 1 , c 2 , c 3 , c 4 ) H 2 , let Bγ=( c 2 + c 3 , c 2 c 3 , c 1 + c 4 ). Then B is a bounded linear operator from H 2 into H 1 with B= 2 . Moreover, for any α=( a 1 , a 2 , a 3 ) H 1 and γ=( c 1 , c 2 , c 3 , c 4 ) H 2 , Aα,γ=α,Bγ, so B is an adjoint operator of A.

Let K be a closed and convex subset of a real Hilbert space H. For each point xH, there exists a unique nearest point in K, denoted by P K x, such that x P K xxy, yK. The mapping P K is called the metric projection from H onto K. It is well known that P K has the following characterizations:

  1. (i)

    xy, P K x P K y P K x P K y 2 for every x,yH.

  2. (ii)

    for xH, and zK, z= P K (x)xz,zy0, yK.

  3. (iii)

    y P K ( x ) 2 + x P K ( x ) 2 x y 2 for all xH and yK.

The following lemmas are crucial in our proofs.

Lemma 2.1 (see [1])

Let K be a nonempty, closed, and convex subset of H and F be a bi-function of K×K into R satisfying the following conditions.

(A1) F(x,x)=0 for all xK;

(A2) F is monotone, that is, F(x,y)+F(y,x)0 for all x,yK;

(A3) for each x,y,zK, lim sup t 0 F(tz+(1t)x,y)F(x,y);

(A4) for each xK, yF(x,y) is convex and lower semicontinuous.

Let r>0 and xH. Then there exists zK such that F(z,y)+ 1 r yz,zx0, for all yK.

Lemma 2.2 (see [3])

Let K be a nonempty, closed, and convex subset of H and let F be a bi-function of K×K into R satisfying (A 1)-(A 4). For r>0, define a mapping T r F :HK as follows:

T r F (x)= { z K : F ( z , y ) + 1 r y z , z x 0 , y K }
(2.1)

for all xH. Then the following hold:

  1. (i)

    T r F is single-valued and F( T r F )=EP(F) for any r>0 and EP(F) is closed and convex;

  2. (ii)

    T r F is firmly nonexpansive, that is, for any x,yH, T r F x T r F y 2 T r F x T r F y,xy.

Lemma 2.3 (see, e.g., [9])

Let H be a real Hilbert space. Then the following hold.

  1. (a)

    x + y 2 y 2 +2x,x+y and x y 2 = x 2 + y 2 2x,y for all x,yH;

  2. (b)

    α x + ( 1 α ) y 2 =α x 2 +(1α) y 2 α(1α) x y 2 for all x,yH and α[0,1].

The following result is simple, but it is very useful in this paper; see also [18].

Lemma 2.4 Let the mapping T r F be defined as (2.1). Then for r,s>0 and x,yH,

T r F ( x ) T s F ( y ) xy+ | s r | s T s F ( y ) y .

In particular, T r F (x) T r F (y)xy for any r>0 and x,yH, that is T r F is nonexpansive for any r>0.

Proof For r,s>0 and x,yH, by (i) of Lemma 2.2, T r F (x)= z 1 and T s F (y)= z 2 for some z 1 , z 2 K. By the definition of T r F , we have

F( z 1 ,u)+ 1 r u z 1 , z 1 x0,uK
(2.2)

and

F( z 2 ,u)+ 1 s u z 2 , z 2 y0,uK.
(2.3)

So, combining (2.2), (2.3), and (A2), we get

1 r z 2 z 1 , z 1 x+ 1 s z 1 z 2 , z 2 y0,

or

z 2 z 1 , z 1 x r z 2 z 1 , z 2 y s 0,

or

z 2 z 1 , s r ( z 1 x ) z 2 z 1 , z 2 y0,

or

z 2 z 1 , z 1 x r s ( z 2 y ) 0,

or

z 2 z 1 , z 1 z 2 + z 2 x r s ( z 2 y ) 0,

which implies

z 2 z 1 2 z 2 z 1 , z 2 x r s ( z 2 y ) z 2 z 1 z 2 x r s ( z 2 y ) ,

and hence

T r F ( x ) T s F ( y ) = z 2 z 1 z 2 x r s ( z 2 y ) y x + ( 1 r s ) ( z 2 y ) = y x + | s r | s T s F ( y ) y .

In particular, the last inequality show that for any r>0, T r F is nonexpansive. The proof is completed. □

3 Main results

In this section, we first introduce a weak convergence iterative algorithms for the split common solution problem.

Theorem 3.1 Let H 1 and H 2 be two real Hilbert spaces and C H 1 and K H 2 be two nonempty closed convex sets. Let T:CC be zero-demiclosed quasi-nonexpansive mappings and f:K×KR be bi-functions with Γ={pF(T):ApEP(f)}. Let A: H 1 H 2 be a bounded linear operator with its adjoint B.

Given x 1 C and η(0,1). Let { x n } and { u n } be sequences generated by

{ u n = T r n f A x n , x n + 1 = ( 1 α n ) y n + α n T y n , y n = P C ( x n + ε B ( T r n f I ) A x n ) , n N ,
(3.1)

where { r n }(0,+) with lim inf n r n >0, ε(0, 1 B 2 ) is a constant, P C is a projection operator from H 1 into C and { α n } satisfies α n [η,1η] for nN. Then x n pΓ and u n ApEP(f).

Proof Let x Γ. Then A x EP(f). For each nN, by Lemmas 2.2 and 2.3, we have

T r n f A x n T r n f A x 2 T r n f A x n T r n f A x , A x n A x = 1 2 { T r n f A x n A x 2 + A x n A x 2 T r n f A x n A x n 2 } .

So,

T r n f A x n A x 2 A x n A x 2 T r n f A x n A x n 2 for any nN.
(3.2)

By (b) of Lemma 2.3 and (3.2), for each nN, we get

(3.3)

Note that for any nN,

B ( T r n f I ) A x n 2 B 2 ( T r n f I ) A x n 2 ,
(3.4)

so it follows from (3.1), (3.3), and (3.4) that

(3.5)

Since ε(0, 1 B 2 ), ε(1ε B 2 )>0, by (3.5), we obtain

x n + 1 x y n x x n x
(3.6)

and

(3.7)

The inequality (3.6) implies that lim n x n x exists. Further, from (3.6) and (3.7), we get

(3.8)
(3.9)

and

lim n ( T r n f I ) A x n =0.
(3.10)

From (3.1) and (3.10), we have

y n x n = P C ( x n + ε B ( T r n f I ) A x n ) P C x n ε B ( T r n f I ) A x n 0 as  n .
(3.11)

Since lim n x n x exists, { x n } is bounded and hence { x n } has a weakly convergence subsequence { x n j }. Assume that x n j p for some pC. Then A x n j ApK, y n j p and T r n j f A x n j Ap by (3.10) and (3.11).

We argue pΓ. Since T is a zero-demiclosed mapping, by (3.9) and y n j p, we obtain pF(T). Applying Lemma 2.2, EP(f)=F( T r f ) for any r>0. We claim T r f Ap=Ap. If T r f ApAp, since A x n T r n f A x n =(I T r n f )A x n 0 as n from (3.10) and applying Opial’s condition, we have

lim inf j A x n j A p < lim inf j A x n j T r f A p = lim inf j A x n j T r n j f A x n j + T r n j f A x n j T r f A p lim inf j { A x n j T r n j f A x n j + T r n j f A x n j T r f A p } = lim inf j T r n j f A x n j T r f A p = lim inf j T r f A p T r n j f A x n j lim inf j ( A x n j A p + | r n j r | r n j T r n j f A x n j A x n j ) ( by Lemma 2.4 ) = lim inf j A x n j A p ,

which lead to a contradiction. So ApF( T r f )=EP(f), and hence we show pΓ.

Now, we prove { x n } converges weakly to pΓ. Otherwise, if there exists other subsequence of { x n } which is denoted by { x n l } such that x n l qΓ with qp. Then, by Opial’s condition,

lim inf l x n l q< lim inf l x n l p< lim inf l x n l q.

This is a contradiction. Hence, { x n } converges weakly to an element pΓ.

Finally, we prove { u n }{ T r n f A x n } converges weakly to ApEP(f). Since x n p, we have A x n Ap as n. Thus, by (3.10), we obtain u n ApEP(f) as n. The proof is completed. □

Corollary 3.1 Let H 1 and H 2 be two real Hilbert spaces. Let T: H 1 H 1 be a zero-demiclosed quasi-nonexpansive mapping with F(T) and f: H 2 × H 2 R be a bi-function with EP(f). Let A: H 1 H 2 be a bounded linear operator with its adjoint B. Given η(0,1). Let { x n } and { u n } be sequences generated by

{ x 1 H 1 , u n = T r n f A x n , x n + 1 = ( 1 α n ) y n + α n T y n , y n = x n + ε B ( T r n f I ) A x n , n N ,
(3.12)

where ε(0, 1 B 2 ) and { r n }(0,+) with lim inf n r n >0. Suppose Γ={pF(T):ApEP(f)} and the control coefficient sequence { α n } satisfies α n [η,1η] for nN. Then the sequence { x n } converges weakly to an element pΓ and { u n } weakly to ApEP(f).

Next, we introduce a strong convergence algorithm for the split common solution problem.

Theorem 3.2 Let C H 1 and K H 2 be two nonempty, closed, and convex sets, T:CC zero-demiclosed quasi-nonexpansive mappings and f:K×KR a bi-function with Γ={pF(T):ApEP(f)}. Let A: H 1 H 2 be a bounded linear operator with the adjoint B. Given x 1 C, C 1 =C and η(0,1). Let { x n } and { u n } be sequences generated by

{ u n = T r n f A x n , y n = ( 1 α n ) z n + α n T z n , z n = P C ( x n + ε B ( T r n f I ) A x n ) ) , C n + 1 = { v C n : y n v z n v x n v } , x n + 1 = P C n + 1 ( x 1 ) , n N ,
(3.13)

where { r n }(0,+) with lim inf n r n >0, P C is a projection operator from H 1 into C and ε(0, 1 B 2 ) is a constant, { α n } satisfies α n [η,1η] for nN, then x n pΓ and u n ApEP(f).

Proof First, we claim Γ C n for nN. In fact, let pΓ. Following the same argument as in Theorem 3.1, we have

2ε x n p , B ( T r n f I ) A x n ε ( T r n f I ) A x n 2 ,
(3.14)

and

B ( T r n f I ) A x n 2 B 2 ( T r n f I ) A x n 2 for any nN.
(3.15)

By (3.13), (3.14), and (3.15), we get

(3.16)

Notice ε(0, 1 B 2 ), ε(1ε B 2 )>0. It follows from (3.16) that

y n p z n p x n pfor all nN,

and hence p C n for all nN. Hence, Γ C n and C n for all nN.

Now, we prove C n is a closed convex set for each nN. It is not hard to verify that C n is closed for each nN, so it suffices to verify that C n is convex for each nN. Indeed, let w 1 , w 2 C n + 1 . For any γ(0,1), since

we have y n (γ w 1 +(1γ) w 2 ) z n (γ w 1 +(1γ) w 2 ). Similarly, we also have z n (γ w 1 +(1γ) w 2 ) x n (γ w 1 +(1γ) w 2 ), which implies γ w 1 +(1γ) w 2 C n + 1 . Hence, we show that C n + 1 is a convex set for each nN.

Notice that C n + 1 C n and x n + 1 = P C n + 1 ( x 1 ) C n , then x n + 1 x 1 x n x 1 for nN with n2. It follows that lim n x n x 1 exists. Hence { x n } is bounded, which yields that { z n } and { y n } are bounded. For any k,nN with k>n, from x k = P C k ( x 1 ) C n and the character (iii) of the projection operator P, we have

x n x k 2 + x 1 x k 2 = x n P C k ( x 1 ) 2 + x 1 P C k ( x 1 ) 2 x n x 1 2 .
(3.17)

Since lim n x n x 1 exists, by (3.17), we have lim n x n x k =0, which implies that { x n } is a Cauchy sequence.

Let x n p. One claim pΓ. Firstly, by x n + 1 = P C n + 1 ( x 0 ) C n + 1 C n , from (3.13) we have

y n x n y n x n + 1 + x n + 1 x n 2 x n + 1 x n 0as n
(3.18)

and

z n x n z n x n + 1 + x n + 1 x n 2 x n + 1 x n 0as n.
(3.19)

Setting ρ=ε(1ε B 2 ), from (3.16) again, we have

ρ ( T r n f I ) A x n 2 + η 2 z n T z n 2 x n p 2 y n p 2 x n y n { x n p + y n p } .

So

lim n T z n z n =0
(3.20)

and

lim n ( T r n f I ) A x n =0.
(3.21)

Let r>0. Since x n p as n, Lemma 2.4 and equation (3.21) imply that

T r f A p A p T r f A p T r n f A x n + T r n f A x n A x n + A x n A p 2 A x n A p + ( 1 + | r n r | r n ) T r n f A x n A x n 0 as  n .

So T r f Ap=Ap, which say that ApF( T r f )=EP(f). On the other hand, since x n z n 0 by (3.19) and x n p, we have z n p. Notice that T is zero-demiclosed quasi-nonexpansive mappings, by (3.20), Tp=p, namely, pF(T). So pΓ. From (3.21), we also have { u n }{ T r n f A x n } converges strongly to ApEP(f). The proof is completed. □

Corollary 3.2 Let H 1 and H 2 be two real Hilbert spaces. Let T: H 1 H 2 be a zero-demiclosed quasi-nonexpansive mappings with F(T) and f:H×HR be a bi-function with EP(f). Let A: H 1 H 2 be a bounded linear operator with the adjoint B. Given x 1 H 1 , C 1 = H 1 , and η(0,1). Let { x n } and { u n } be sequences generated by

{ u n = T r n f A x n , y n = ( 1 α n ) z n + α n T z n , z n = x n + ε B ( T r n f I ) A x n , C n + 1 = { v C n : y n v z n v x n v } , x n + 1 = P C n + 1 ( x 1 ) , n N ,
(3.22)

where { r n }(0,+) with lim inf n r n >0, and ε(0, 1 B 2 ) is a constant. Suppose that Γ={pF(T):ApEP(f)} and the control coefficient sequence { α n } satisfies α n [η,1η] for nN, then the sequence { x n } converges strongly to an element pΓ and { u n } converges strongly to ApEP(f).

Example 3.1 Let H 1 = H 2 =R with the inner product defined by x,y=xy for all x,yR and the standard norm ||. Let C:=[0,+) and Tx= x 2 + 2 1 + x for all xC. From Examples 2.1 and 2.2, we know that T is an zero-demiclosed quasi-nonexpansive mapping with F(T)={2}.

Let K:=[,0] and f 1 (x,y)=(yx)(x+4) for all x,yK, then f satisfies the condition (A1)-(A4) and EP(f)={4}. Let Ax=2x for all xR, then A is a bounded linear operator with B (the adjoint of A) =A and A=B=2.

Obviously, Γ={pF(T):ApEP(f)}={2}=F(T), so Γ. Let x 1 C, { x n } and { u n } be sequences generated by

{ u n = T r n f A x n , x n + 1 = ( 1 α n ) y n + α n T y n , y n = P C ( x n + 1 8 B ( T r n f I ) A x n ) , n N ,
(3.23)

where, r n =1 and α n (0,1) for all nN, P C is a projection operator from H 1 into C. Then the sequence { x n } converges strongly to 2Γ and { u n } converges strongly to A(2)=4EP(f).

Proof

  1. (i)

    Firstly, for given r n =1 for nN, we prove that for any { x n }C, there exists a unique sequence { u n } n N { x n 2 } n N in K such that

    f( u n ,v)+v u n , u n A x n 0,vK,nN.
    (3.24)

Because (3.24) is equivalent with

(3.25)

while (3.25) is true if and only if u n =( x n +2) for all nN. So the conclusion is true.

  1. (ii)

    Secondly, it is not hard to compute B( T r n f I)A x n =B( u n A x n )=2( x n 2) for all nN. Hence,

    x n + 1 8 B ( T r n f I ) A x n = 3 4 x n + 1 2 Cfor all nN.
  2. (iii)

    By (i) and (ii), for x 1 C, we can rewrite the algorithm (3.23) as follows:

    x n + 1 =(1 α n ) y n + α n T y n , y n = 3 4 x n + 1 2
    (3.26)

and

u n = T r n f A x n =( x n +2),nN.
(3.27)

As in Example 2.1, we easily obtain |T y n 2|| y n 2|. Hence, from (3.26) and (3.27), we get

| x n + 1 2 | ( 1 α n ) | y n 2 | + α n | T y n 2 | | y n 2 | = 3 4 | x n 2 | ( 3 4 ) n | x 1 2 | , n N ,

which shows x n 2F(T)=Γ. Since u n =( x n +2), nN, we obtain u n 4=A(2)EP(f).

 □

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Acknowledgements

The authors would like to express their sincere thanks to the anonymous referee for their valuable comments and useful suggestions in improving the paper. The first author was supported by the Natural Science Foundation of Yunnan Province (2010ZC152). The second author was supported partially by Grant no. NSC 100-2115-M-017-001 of the National Science Council of the Republic of China.

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Both authors contributed equally and significantly in writing this paper. Both authors read and approved the final manuscript.

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He, Z., Du, WS. Nonlinear algorithms approach to split common solution problems. Fixed Point Theory Appl 2012, 130 (2012). https://doi.org/10.1186/1687-1812-2012-130

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