1 Introduction

Let X be a real Banach space with the dual space X . The value of f X at xX is denoted by x,f. The normal duality mapping J from X into a family of nonempty (by the Hahn-Banach theorem) weak-star compact subsets of X is defined by

J(x)= { f X : x , f = x 2 = f 2 } ,xX.

Let U={xX:x=1}. A Banach space X is said to be uniformly convex if for each ϵ(0,2], there exists δ>0 such that for any x,yU,

xyϵimplies x + y 2 1δ.

It is known that a uniformly convex Banach space is reflexive and strictly convex. A Banach space X is said to be smooth if the limit

lim t 0 x + t y x t
(1.1)

exists for all x,yU. It is said to be uniformly smooth if limit (1.1) is attained uniformly for x,yU. It is well known that if X is smooth, then J is single-valued and continuous from the norm topology of X to the weak-star topology of X , i.e., norm to weak continuous. It is also well known that if X is uniformly smooth, then J is uniformly continuous on bounded subsets of X from the strong topology of X to the strong topology of X , i.e., uniformly norm-to-norm continuous on any bounded subset of X; see [1, 2] for more details.

Also, we define a function ρ:[0,)[0,) called the modulus of smoothness of X as follows:

ρ(τ)=sup { 1 2 ( x + y + x y ) 1 : x , y X , x = 1 , y = τ } .

It is known that X is uniformly smooth if and only if lim τ 0 ρ(τ)/τ=0. Let q be a fixed real number with 1<q2. Then a Banach space X is said to be q-uniformly smooth if there exists a constant c>0 such that ρ(τ)c τ q for all τ>0. One should note that no Banach space is q-uniformly smooth for q>2; see [3] for more details. So, in this paper, we focus on a 2-uniformly smooth Banach space. It is well known that Hilbert spaces and Lebesgue L p (p2) spaces are uniformly convex and 2-uniformly smooth.

Recall that a mapping T:XX is said to be nonexpansive if

TxTyxy,x,yX.

A point xX is a fixed point of T if Tx=x. Let Fix(T) denote the set of fixed points of T; that is, Fix(T)={xX:Tx=x}.

A mapping f ¯ :XX is called strongly pseudo-contractive if there exists a constant ρ(0,1) and j(xy)J(xy) satisfying

f ¯ ( x ) f ¯ ( y ) , j ( x y ) ρ x y 2 ,x,yX.

A mapping f:XX is a contraction if there exists a constant α(0,1) such that

f ( x ) f ( y ) αxy,x,yX.

Since f(x)f(y),j(xy)f(x)f(y)xyα x y 2 , we have that f is a strong pseudo-contraction.

Let η>0, a mapping F ¯ of X into X is said to be η-strongly accretive if there exists j(xy)J(xy) such that

F ¯ x F ¯ y , j ( x y ) η x y 2

for all x,yX. A mapping F ¯ of X into X is said to be k-Lipschitzian if, for k>0,

F ¯ x F ¯ ykxy

for all x,yX. It is well known that if X is a Hilbert space, then an η-strongly accretive operator coincides with an η-strongly monotone operator.

Yamada [4] introduced the following hybrid iterative method for solving the variational inequality in a Hilbert space:

x n + 1 =T x n μ λ n F(T x n ),n0,
(1.2)

where F is a k-Lipschitzian and η-strongly monotone operator with k>0, η>0 and 0<μ<2η/ k 2 . Let a sequence { λ n } of real numbers in (0,1) satisfy the conditions below:

( A 1 ) lim n λ n = 0 , ( A 2 ) n = 0 λ n = , ( A 3 ) lim n ( λ n λ n + 1 ) / λ n + 1 2 = 0 .

He proved that { x n } generated by (1.2) converges strongly to the unique solution of the variational inequality

F x ˜ ,x x ˜ 0,xFix(T).

An example of sequence { λ n } which satisfies conditions (A1)-(A3) is given by λ n =1/ n σ , where 0<σ<1. We note that condition (A3) was first used by Lions [5]. It was observed that Lion’s conditions on the sequence { λ n } excluded the canonical choice λ n =1/n. This was overcome in 2003 by Xu and Kim [6] in a Hilbert space. They proved that if { λ n } satisfies conditions (A1), (A2) and (A4)

(A4) lim n λ n / λ n + 1 =1or, equivalently, lim n ( λ n λ n + 1 )/ λ n + 1 =0,

then { x n } is strongly convergent to the unique solution u of the variational inequality F u ,v u 0, vC. It is easy to see that condition (A4) is strictly weaker than condition (A3), coupled with conditions (A1) and (A2). Moreover, (A4) includes the important and natural choice {1/n} of { λ n }.

In 2010, Tian [7] improved Yamada’s method (1.2) and established the following strong convergence theorems.

Theorem 1.1 ([[7], Theorem 3.1])

Let H be a Hilbert space. Let T:HH be a nonexpansive mapping with Fix(T), and let f:HH be a contraction mapping with α(0,1). Assume that { x t } is defined by

x t =tγf( x t )+(ItμF)T x t ,
(1.3)

where F is a k-Lipschitzian and η-strongly monotone operator on a Hilbert space H with k>0, η>0. Let 0<μ<2η/ k 2 , 0<γ<μ(η μ k 2 2 )/α=τ/α and 0<t<1. Then x t converges strongly as t0 to a fixed point x ˜ of T, which solves the variational inequality (μFγf) x ˜ , x ˜ z0, zFix(T).

Theorem 1.2 ([[7], Theorem 3.1])

Let H be a Hilbert space. Let T:HH be a nonexpansive mapping with Fix(T), let f:HH be a contraction mapping with α(0,1), and let F be a k-Lipschitzian and η-strongly monotone operator on H with k>0, η>0 and 0<μ<2η/ k 2 . For an arbitrary x 0 H, let { x n } be generated by

x n + 1 =(I α n μF)T x n + α n γf( x n ),n0,
(1.4)

where 0<γ<μ(η μ k 2 2 )/α=τ/α and { α n }(0,1) satisfies

(C1) α n 0,

(C2) n = 0 α n =,

(C3) either n = 0 | α n + 1 α n |< or lim n α n + 1 α n =1.

Then { x n } converges strongly to x ˜ that is obtained in Theorem  1.1.

We remind the reader of the following facts: (i) The results are obtained when the underlying space is a Hilbert space in Yamada [4], Xu [6] and Tian [7]. (ii) In order to guarantee the strong convergence of the iterative sequence { x n }, there is at least one parameter sequence converging to zero (i.e., α n or λ n 0) in Yamada [4], Xu [6] and Tian [7]. (iii) The parameter sequence satisfies the condition lim n λ n / λ n + 1 =1 (or lim n α n + 1 / α n =1).

In this paper, we establish a necessary and sufficient condition for the strong convergence of { x n } generated by (3.7) (defined below) in a uniformly convex and 2-uniformly smooth Banach space. In the meantime, we remove the control condition (C1) and replace condition (C3) with (C3′) (defined below) in the result of Tian [7]. It is worth pointing out that we use a new method to prove our main results. The results presented in this paper can be viewed as an improvement, supplement and extension of the results obtained in [4, 6, 7].

2 Preliminaries

For the sequence { x n } in X, we write x n x to indicate that the sequence { x n } converges weakly to x. x n x means that { x n } converges strongly to x. In order to prove our main results, we need the following lemmas.

Lemma 2.1 ([8])

Let q be a given real number with 1<q2, and let X be a q-uniformly smooth Banach space. Then

x + y q x q +q y , J q ( x ) +2 K y q

for all x,yX, where K is a q-uniformly smooth constant of X and J q is the generalized duality mapping from X into 2 X defined by

J q (x)= { f X : x , f = x q , f = x q 1 }

for all xX.

Lemma 2.2 ([2])

Let C be a nonempty bounded closed convex subset of a uniformly convex Banach space X, and let T be a nonexpansive mapping of C into itself. If { x n } is a sequence of C such that x n x and x n T x n 0, then x is a fixed point of T.

Lemma 2.3 ([9, 10])

Let { s n } be a sequence of nonnegative real numbers satisfying

s n + 1 (1 λ n ) s n + λ n δ n + γ n ,n0,

where { λ n }, { δ n } and { γ n } satisfy the following conditions: (i) { λ n }[0,1] and n = 0 λ n =, (ii) lim sup n δ n 0 or n = 0 λ n δ n <, (iii) γ n 0 (n0), n = 0 γ n <. Then lim n s n =0.

The following lemma is easy to prove.

Lemma 2.4 Let X be a Banach space, let f ¯ :XX be a strongly pseudo-contractive operator with 0<ρ<1, and let F ¯ :XX be a k-Lipschitzian and η-strongly accretive operator with k>0, η>0. Then, for ρ<μη,

( μ F ¯ f ¯ ) x ( μ F ¯ f ¯ ) y , j ( x y ) (μηρ) x y 2 ,x,yX,

that is, μ F ¯ f ¯ is a strongly accretive operator with coefficient μηρ.

Lemma 2.5 Let X be a real 2-uniformly smooth Banach space. Let t be a number in (0,1), and let μ>0. Let F ¯ :XX be an operator such that, for some constant 0<η 2 kK, F ¯ is k-Lipschitzian and η-strongly accretive. Then S=(Itμ F ¯ ):XX is a contraction provided μη/(2 k 2 K 2 ), that is,

SxSy(1tτ)xy,x,yX,

where τ=1 1 2 μ η + 2 μ 2 k 2 K 2 (0,1].

Proof Using Lemma 2.1, we have

( I μ F ¯ ) x ( I μ F ¯ ) y 2 x y 2 2 μ F ¯ x F ¯ y , j ( x y ) + 2 μ 2 K 2 F ¯ x F ¯ y 2 x y 2 2 μ η x y 2 + 2 μ 2 K 2 k 2 x y 2 = ( 1 2 μ η + 2 μ 2 k 2 K 2 ) x y 2 .

It follows from 0<η 2 kK and 0<μη/(2 k 2 K 2 ) that

( I μ F ¯ ) x ( I μ F ¯ ) y 1 2 μ η + 2 μ 2 k 2 K 2 xy

for all x,yX. Therefore, we have

S x S y = ( 1 t ) ( x y ) t [ ( I μ F ¯ ) y ( I μ F ¯ ) x ] ( 1 t ) x y + t ( I μ F ¯ ) x ( I μ F ¯ ) y ( 1 t ) x y + t 1 2 μ η + 2 μ 2 k 2 K 2 x y = ( 1 t τ ) x y ,

where τ=1 1 2 μ η + 2 μ 2 k 2 K 2 (0,1]. □

3 Main results

Throughout this section, let X be a uniformly convex and 2-uniformly smooth Banach space. Let T:XX be a nonexpansive mapping with Fix(T). Let F ¯ :XX be a k-Lipschitzian and η-strongly accretive operator with 0<η 2 kK. Let μ(0,η/(2 k 2 K 2 )] and τ=1 1 2 μ η + 2 μ 2 k 2 K 2 . Let f ¯ :XX be a Lipschitzian and strongly pseudo-contractive operator with 0<ρ<τ. Let t be a number in (0,1). Consider a mapping S t on X defined by

S t x=t f ¯ (x)+(Itμ F ¯ )Tx,xX.

It is easy to see that the mapping S t is strongly pseudo-contractive. Indeed, from Lemma 2.5, we have

S t x S t y , j ( x y ) = t f ¯ ( x ) f ¯ ( y ) , j ( x y ) + ( I t μ F ¯ ) T x ( I t μ F ¯ ) T y , j ( x y ) t ρ x y 2 + ( I t μ F ¯ ) T x ( I t μ F ¯ ) T y x y t ρ x y 2 + ( 1 t τ ) x y 2 [ 1 t ( τ ρ ) ] x y 2

for all x,yX. Since f ¯ is Lipschitzian and Itμ F ¯ is contractive, hence S t is continuous. So, by Deimling [11], we can obtain that S t has a unique fixed point which we denoted by x t , that is,

x t =t f ¯ ( x t )+(Itμ F ¯ )T x t , x t X.
(3.1)

Our first main result below shows that { x t } converges strongly as t 0 + to a fixed point of T which solves some variational inequality.

Theorem 3.1 { x t } generated by the implicit method (3.1) converges in norm as t 0 + to the unique solution x Fix(T) of the variational inequality

( μ F ¯ f ¯ ) x , j ( x u ) 0,uFix(T).
(3.2)

Proof It is easy to see the uniqueness of a solution of variational inequality (3.2). By Lemma 2.4, μ F ¯ f ¯ is strongly accretive, so variational inequality (3.2) has only one solution. Below we use x Fix(T) to denote the unique solution of (3.2).

Next, we prove that { x t } is bounded. Take uFix(T), from (3.1) and using Lemma 2.5, we have

x t u 2 = x t u , j ( x t u ) = t f ¯ ( x t ) f ¯ ( u ) , j ( x t u ) + ( I t μ F ¯ ) T x t ( I t μ F ¯ ) T u , j ( x t u ) + t f ¯ ( u ) μ F ¯ u , j ( x t u ) t ρ x t u 2 + ( I t μ F ¯ ) T x t ( I t μ F ¯ ) T u x t u + t f ¯ ( u ) μ F ¯ u x t u [ 1 t ( τ ρ ) ] x t u 2 + t f ¯ ( u ) μ F ¯ u x t u .

It follows that

x t u 1 τ ρ f ¯ ( u ) μ F ¯ u .

Therefore, { x t } is bounded, and so are the nets { f ¯ ( x t )} and { F ¯ T x t }.

On the other hand, from (3.1) we obtain

x t T x t =t f ¯ ( x t ) μ F ¯ T x t 0 ( t 0 + ) .
(3.3)

Next, we show that { x t } is relatively norm-compact as t 0 + . Assume that { t n }(0,1) such that t n 0 + as n. Put x n := x t n . It follows from (3.3) that

x n T x n 0(n).
(3.4)

For a given uFix(T), by (3.1) and using Lemma 2.5, we have

x t u 2 = x t u , j ( x t u ) = t f ¯ ( x t ) f ¯ ( u ) , j ( x t u ) + ( I t μ F ¯ ) T x t ( I t μ F ¯ ) T u , j ( x t u ) + t f ¯ ( u ) μ F ¯ u , j ( x t u ) [ 1 t ( τ ρ ) ] x t u 2 + t f ¯ ( u ) μ F ¯ u , j ( x t u ) ,

that is,

x t u 2 1 τ ρ f ¯ ( u ) μ F ¯ u , j ( x t u ) .

In particular,

x n u 2 1 τ ρ f ¯ ( u ) μ F ¯ u , j ( x n u ) .
(3.5)

Since { x t } is bounded, without loss of generality, we may assume that { x n } converges weakly to a point x ˜ . By (3.4) and using Lemma 2.2, we have x ˜ Fix(T). Then by (3.5), x n x ˜ . This has proved the relative norm compactness of the net { x t } as t 0 + .

We next show that x ˜ solves variational inequality (3.2). Observe that

(μ F ¯ f ¯ )( x t )= 1 t (IT) x t +μ( F ¯ x t F ¯ T x t ).

Since IT is accretive (this is due to the nonexpansiveness of T), for any uFix(T), we can deduce immediately that

( I T ) x t ( I T ) u , j ( x t u ) 0.

Therefore, for any uFix(T),

( μ F ¯ f ¯ ) ( x t ) , j ( x t u ) = 1 t ( I T ) x t , j ( x t u ) + μ F ¯ x t F ¯ T x t , j ( x t u ) = 1 t ( I T ) x t ( I T ) u , j ( x t u ) + μ F ¯ x t F ¯ T x t , j ( x t u ) μ F ¯ x t F ¯ T x t , j ( x t u ) .
(3.6)

Now, replace t in (3.6) with t n . Noting that F ¯ x t n F ¯ T x t n F ¯ x ˜ F ¯ x ˜ =0 for x ˜ Fix(T) as n, we have

( μ F ¯ f ¯ ) x ˜ , j ( x ˜ u ) 0.

That is x ˜ Fix(T) is a solution of (3.2), hence x ˜ = x by uniqueness. In summary, we have shown that each cluster point of { x t } (as t 0 + ) equals x . Therefore, x t x as t 0 + . □

Remark 3.2 Compared with Theorem 3.1 of Tian [7], our Theorem 3.1 improves and extends Theorem 3.1 of Tian [7] in the following aspects:

  1. (i)

    The framework of a Hilbert space is extended to a uniformly convex and 2-uniformly smooth Banach space.

  2. (ii)

    The η-strongly monotone operator F is extended to the case of an η-strongly accretive operator F ¯ . The contraction f:HH is extended to the case of a Lipschitzian and strongly pseudo-contractive operator f ¯ :XX.

  3. (iii)

    If we put X=H, F ¯ =F and f ¯ =γf, then our Theorem 3.1 reduces to Theorem 3.1 of Tian [7]. Thus, our Theorem 3.1 covers Theorem 3.1 of Tian [7] as a special case.

Next we consider the following iteration process: the initial guess x 0 is selected in X arbitrarily and the (n+1)th iterate x n + 1 is defined by

x n + 1 =(I α n μ F ¯ )T x n + α n γf( x n ),n0,
(3.7)

where f:XX is a contractive mapping with 0<γα<τ, { α n } is a sequence in (0,1) satisfying conditions (C2) and

(C3′) | α n + 1 α n |o( α n + 1 )+ σ n with σ n 0 and n = 0 σ n <.

Besides the basic condition (C2) on the sequence α n , we have the control condition (C3′). It can obviously be replaced by one of the following:

(C3-1) n = 0 | α n + 1 α n |<;

(C3-2) lim n α n + 1 / α n =1.

Indeed, (C3-1) implies (C3′) by choosing σ n =| α n + 1 α n |, and (C3-2) implies (C3′) by choosing σ n =0. In this sense (C3′) is a weaker condition than the previous condition (C3).

Our second main result below shows that we have established a necessary and sufficient condition for the strong convergence of nonexpansive mappings in a uniformly convex and 2-uniformly smooth Banach space.

Theorem 3.3 Let { x n } be generated by algorithm (3.7) with the sequence α n of parameters satisfying conditions (C2) and (C3′). Then

x n x α n ( γ f ( x n ) μ F ¯ T x n ) 0(n),

where x Fix(T) solves the variational inequality (μ F ¯ γf) x ,j( x u)0, uFix(T).

Proof On the one hand, suppose that α n (γf( x n )μ F ¯ T x n )0 (n). We proceed with the following steps.

Step 1. We claim that { x n } is bounded. In fact, taking uFix(T), from (3.7) and using Lemma 2.5, we have

x n + 1 u = α n ( γ f ( x n ) γ f ( u ) ) + ( I α n μ F ¯ ) T x n ( I α n μ F ¯ ) T u + α n ( γ f ( u ) μ F ¯ u ) α n γ α x n u + ( 1 α n τ ) x n u + α n γ f ( u ) μ F ¯ u = [ 1 α n ( τ γ α ) ] x n u + α n ( τ γ α ) γ f ( u ) μ F ¯ u τ γ α max { x n u , γ f ( u ) μ F ¯ u τ γ α } .

By induction, we have

x n umax { x 0 u , γ f ( u ) μ F ¯ u τ γ α } .

Therefore, { x n } is bounded. We also obtain that {f( x n )} and { F ¯ T x n } are bounded.

Step 2. We claim that lim n x n + 1 x n =0. Observe that

x n + 1 x n = α n γ ( f ( x n ) f ( x n 1 ) ) + γ ( α n α n 1 ) f ( x n 1 ) + ( I α n μ F ¯ ) T x n ( I α n μ F ¯ ) T x n 1 + ( α n 1 α n ) μ F ¯ T x n 1 [ 1 α n ( τ γ α ) ] x n x n 1 + M | α n α n 1 | [ 1 α n ( τ γ α ) ] x n x n 1 + M o ( α n ) + M σ n 1 ,

where M=max{γf( x n 1 ),μ F ¯ T x n 1 }. By Lemma 2.3, we have lim n x n + 1 x n =0.

Step 3. We claim that lim n x n T x n =0. Indeed, from Step 2, we have

x n T x n x n x n + 1 + x n + 1 T x n = x n x n + 1 + α n ( γ f ( x n ) μ F ¯ T x n ) 0 ( n ) .

Step 4. We claim that lim sup n (γfμ F ¯ ) x ,j( x n + 1 x )0, where x = lim t 0 + x t and x t is defined by x t =tγf( x t )+(Itμ F ¯ )T x t . Since { x n + 1 } is bounded, there exists a subsequence { x { n + 1 } k } of { x n + 1 } which converges weakly to ω. From Step 3, we obtain T x { n + 1 } k ω. From Lemma 2.2, we have ωFix(T). Since f is a contractive mapping, we have that γf is a Lipschitzian and strongly pseudo-contractive operator with γα(0,τ). Hence, using Theorem 3.1, we have x Fix(T) and

lim sup n ( γ f μ F ¯ ) x , j ( x n + 1 x ) = lim k ( γ f μ F ¯ ) x , j ( x { n + 1 } k x ) = ( γ f μ F ¯ ) x , j ( ω x ) 0 .

Step 5. We claim that { x n } converges strongly to x Fix(T). From (3.7) and using Lemma 2.5, we have

x n + 1 x 2 = ( I α n μ F ¯ ) T x n + α n γ f ( x n ) x , j ( x n + 1 x ) = ( I α n μ F ¯ ) T x n ( I α n μ F ¯ ) T x , j ( x n + 1 x ) + α n γ f ( x n ) μ F ¯ x , j ( x n + 1 x ) ( 1 α n τ ) x n x x n + 1 x + α n γ α x n x x n + 1 x + α n γ f ( x ) μ F ¯ x , j ( x n + 1 x ) [ 1 α n ( τ γ α ) ] x n x x n + 1 x + α n γ f ( x ) μ F ¯ x , j ( x n + 1 x ) [ 1 α n ( τ γ α ) ] 2 2 x n x 2 + 1 2 x n + 1 x 2 + α n γ f ( x ) μ F ¯ x , j ( x n + 1 x ) .

It follows that

x n + 1 x 2 [ 1 α n ( τ γ α ) ] x n x 2 + 2 α n γ f ( x ) μ F ¯ x , j ( x n + 1 x ) ( 1 μ n ) x n x 2 + μ n δ n ,

where μ n = α n (τγα) and δ n = 2 τ γ α γf( x )μ F ¯ x ,j( x n + 1 x ). It is easy to see that n = 1 μ n = and lim sup n δ n 0. Hence, by Lemma 2.3, the sequence { x n } converges strongly to x Fix(T). From x = lim t 0 x t and Theorem 3.1, we have that x is the unique solution of the variational inequality (μ F ¯ γf) x ,j( x u)0, uFix(T).

On the other hand, suppose that x n x Fix(T) as n, where x is the unique solution of the variational inequality (μ F ¯ γf) x ,j( x u)0, uFix(T). Observe that

α n ( γ f ( x n ) μ F ¯ T x n ) = x n + 1 T x n x n + 1 x + T x T x n x n + 1 x + x n x 0 ( n ) .

This completes the proof. □

Remark 3.4 Compared with Theorem 3.2 of Tian [7], our Theorem 3.3 improves and extends Theorem 3.1 of Tian [7] in the following aspects:

  1. (i)

    The framework of a Hilbert space is extended to a uniformly convex and 2-uniformly smooth Banach space.

  2. (ii)

    The η-strongly monotone operator F is extended to the case of an η-strongly accretive operator F ¯ .

  3. (iii)

    We establish a necessary and sufficient condition for the strong convergence of nonexpansive mappings. It follows from (C1) that α n (γf( x n )μ F ¯ T x n )0 (n). Hence, we can obtain Theorem 3.2 of Tian [7] immediately. Thus, our Theorem 3.3 covers Theorem 3.1 of Tian [7] as a special case.

The following example shows that all the conditions of Theorem 3.3 are satisfied. However, condition (C1) is not satisfied.

Example 3.5 Let X=R be the set of real numbers. Define the mappings T:XX, f:XX and F ¯ :XX as follows:

Tx=0, F ¯ x=xandf(x)= 1 2 xxR.

It is easy to see that K= 2 2 , α= 1 2 and Fix(T)={0}. By F ¯ x=x, we have η=k=1 and hence 0<μη/(2 k 2 K 2 )=1. Also, put μ=1. It is easy to see that τ=1 1 2 μ η + 2 μ 2 k 2 K 2 =1. From 0<γα<τ, we have γ(0,2). Without loss of generality, we put γ=1. Given sequences { α n } and { σ n }, α n =1/2, o( α n + 1 )=1/ n 2 and σ n =0 for all n0. For an arbitrary x 0 X, let { x n } be defined as

x n + 1 =(I α n μ F ¯ )T x n + α n γf( x n ),n0,

that is,

x n + 1 = 1 2 1 2 x n = 1 4 x n ,n0.

Observe that for all n0,

x n + 1 0= 1 4 x n 0.

Hence we have x n + 1 0= ( 1 4 ) n + 1 x 0 0 for all n0. This implies that { x n } converges strongly to 0Fix(T).

Observe that (μ F ¯ γf)0,j(0u)0, uFix(T), that is, 0 is the solution of the variational inequality (μ F ¯ γf) x ,j( x u)0, uFix(T).

Finally, we have

α n ( γ f ( x n ) μ F ¯ T x n ) = 1 2 ( 1 2 x n 0 ) = 1 4 x n 0(n).

Hence there is no doubt that all the conditions of Theorem 3.3 are satisfied. Since α n =1/2, condition (C1): lim n α n =0 of Tian [7] is not satisfied.