Let H be a real Hilbert space with the inner product \(\langle\cdot ,\cdot\rangle\), which induces the norm \(\|\cdot\|\).
Let C be a nonempty, closed, and convex subset of H. Let T be a nonlinear mapping of C into itself; we denote with \(\operatorname{Fix}(T)\) the set of fixed points of T, that is, \(\operatorname{Fix}(T)=\{z\in C: Tz=z\}\).
We recall that a mapping \(T:C\rightarrow C\) is said to be k-strict pseudo-contractive (in the sense of Browder-Petryshyn) if there exists \(k\in[0,1)\) such that
$$ \Vert Tx-Ty\Vert ^{2}\leq \Vert x-y\Vert ^{2}+k\bigl\Vert (I-T)x-(I-T)y\bigr\Vert ^{2}, \quad \forall x,y \in C. $$
(1.1)
Note that the class of strict pseudo-contractions includes the class of nonexpansive mappings, which are mappings T on C such that
$$ \|Tx-Ty\|\leq\|x-y\|, \quad \forall x,y \in C. $$
The problem of finding fixed points of nonexpansive mappings via Mann’s algorithm [2] has been widely investigated in the literature (see e.g. [3]).
Mann’s algorithm generates, on initializing with an arbitrary \(x_{1}\in C\), a sequence according to the recursive formula
$$ x_{1}\in C, \quad x_{n+1}=\alpha_{n} x_{n}+(1-\alpha_{n})Tx_{n},\quad \forall n\geq1, $$
(1.2)
where \((\alpha_{n})_{n\in\mathbb{N}}\subset(0,1)\).
If \(T:C\rightarrow C\) is a nonexpansive mapping with a fixed point in a closed and convex subset of a uniformly convex Banach space with a Frechét differentiable norm, and if the control sequence \((\alpha _{n})_{n\in\mathbb{N}}\) is chosen so that \(\sum_{n=1}^{\infty}\alpha _{n}(1-\alpha _{n})=\infty\), then the sequence \((x_{n})\) generated by Mann’s algorithm converges weakly to a fixed point of T [3]. However, this convergence is in general not strong (see the counterexample in [4]).
On the other hand, iterative algorithms for strict pseudo-contractions are still less developed than those for nonexpansive mappings, despite the pioneering work of Browder and Petryshyn [5] dating from 1967. However, strict pseudo-contractions have many applications, due to their ties with inverse strongly monotone operators. Indeed, if A is a strongly monotone operator, then \(T=I-A\) is a strict pseudo-contraction, and so we can redraft a problem of zeros for A in a fixed point problem for T, and vice versa (see e.g. [6, 7]).
The Mann algorithm has weak convergence also in the broader setting of strict pseudo-contractions mapping, containing the nonexpansive mappings.
Theorem 1.1
(Marino and Xu [8], 2007, Mann’s method)
Let
C
be a closed and convex subset of a Hilbert space
H. Let
\(T:C\rightarrow C\)
be a
k-strict pseudo-contraction for some
\(0\leq k<1\). Assume that
T
admits a fixed point in
C. Let
\((x_{n})\)
be the sequence generated by
\(x_{0}\in C\)
and the Mann algorithm
$$ x_{n+1}=\alpha_{n}x_{n}+ (1-\alpha_{n} )Tx_{n}. $$
Assume that the control sequence
\((\alpha_{n})\)
is chosen so that
\(k<\alpha_{n}<1\)
for all
n
and
$$ \sum_{n=0}^{+\infty} (\alpha_{n}-k ) (1-\alpha _{n} )=+\infty. $$
Then
\((x_{n})\)
converges weakly to a fixed point of
T.
It is not possible, in general, to obtain strong convergence, in view of the celebrated counterexample of Genel and Lindenstrauss [4].
So, to obtain strong convergence, one can try to modify the Mann algorithm and strengthen the hypotheses on the mapping.
We recall here some obtained results.
Theorem 1.2
(Li et al. [9], 2013, modified Halpern’s method)
Let
C
be a closed and convex subset of a real Hilbert space
H, \(T:C\rightarrow C\)
be a
k-strict pseudo-contraction such that
\(\operatorname{Fix}(T)\neq\emptyset\). For an arbitrary initial value
\(x_{0}\in C\)
and fixed anchor
\(u\in C\), define iteratively a sequence
\((x_{n})\)
as follows:
$$ x_{n+1}=\alpha_{n}u+\beta_{n}x_{n}+ \gamma_{n}Tx_{n}, $$
where
\((\alpha_{n})\), \((\beta_{n})\), \((\gamma_{n})\)
are three real sequences in
\((0,1)\)
satisfying
\(\alpha_{n}+\beta_{n}+\gamma_{n}=1\)
and
\(0< k<\frac {\beta_{n}}{\beta_{n}+\gamma_{n}}\). Suppose that
\((\alpha_{n})\)
satisfies the conditions:
$$\lim_{n\to\infty}\alpha_{n}=0 , \qquad \sum _{n=1}^{+\infty}\alpha _{n}=+\infty. $$
Then
\((x_{n})\)
converges strongly to
\(x^{*}=P_{\operatorname{Fix}(T)}u\), where
\(P_{\operatorname{Fix}(T)}\)
is the metric projection from
H
onto
\(\operatorname{Fix}(T)\).
Theorem 1.3
(Marino and Xu [8], 2007, CQ method)
Let
C
be a closed convex subset of a Hilbert space
H. Let
\(T:C\rightarrow C\)
be a
k-strict pseudo-contraction for some
\(0\leq k<1\)
and assume that
\(\operatorname{Fix}(T)\neq\emptyset\). Let
\((x_{n})\)
be the sequence generated by the following (CQ) algorithm:
$$\left \{ \textstyle\begin{array}{l} x_{0}\in C, \\ y_{n}=\alpha_{n}x_{n}+ (1-\alpha_{n} )Tx_{n}, \\ C_{n}= \{z\in C: \Vert y_{n}-z\Vert ^{2}\leq \Vert x_{n}-z\Vert ^{2}+ (1-\alpha_{n} ) (k-\alpha_{n} )\Vert x_{n}-Tx_{n}\Vert ^{2} \}, \\ Q_{n}= \{z\in C: \langle x_{n}-z, x_{0}-x_{n} \rangle \geq 0 \}, \\ x_{n+1}=P_{C_{n}\cap D_{n}}x_{0}. \end{array}\displaystyle \right . $$
Assume that the control sequence
\((\alpha_{n})\)
is chosen so that
\(\alpha_{n}<1\)
for all
n. Then
\((x_{n})\)
converges strongly to
\(P_{\operatorname{Fix}(T)}x_{0}\).
Theorem 1.4
(Shang [10], 2007, viscosity method)
Let
C
be a closed convex subset of a Hilbert space
H
and let
\(T:C\rightarrow C\)
be a
k-strict pseudo-contraction with
\(\operatorname{Fix}(T)\neq \emptyset\). Let
\(f:C\rightarrow C\)
be a contraction. The initial value
\(x_{0}\in C\)
is chosen arbitrarily, and we have sequences
\((\alpha_{n})\)
and
\((\beta_{n})\)
satisfying the following conditions:
-
(1)
\(\lim_{n\to\infty}\alpha_{n}=0\), \(\sum_{n=1}^{+\infty }\alpha _{n}=+\infty\);
-
(2)
\(0< a<\beta_{n}<\gamma\)
for some
\(a\in(0,\gamma]\)
and
\(\gamma =\min \{1,2k \}\);
-
(3)
\(\sum_{n=1}^{+\infty} \vert \alpha_{n+1}-\alpha_{n} \vert <+\infty \)
and
\(\sum_{n=1}^{+\infty} \vert \beta_{n+1}-\beta_{n} \vert <+\infty\).
Let
\((x_{n})\)
be the composite process defined by
$$\left \{ \textstyle\begin{array}{l} y_{n}= (1-\beta_{n} )x_{n}+\beta_{n}Tx_{n}, \\ x_{n+1}=\alpha_{n}f(x_{n})+ (1-\alpha_{n} )y_{n}. \end{array}\displaystyle \right . $$
Then
\((x_{n})\)
converges strongly to a fixed point
\(p\in \operatorname{Fix}(T)\).
Theorem 1.5
(Osilike and Udomene [11], 2001, Ishikawa type method)
Let
H
be a Hilbert space. Let
C
be a nonempty, closed, and convex subset of
H, \(T:C\rightarrow C\)
a demicompact
k-strict pseudo-contraction with
\(\operatorname{Fix}(T)\neq\emptyset\). Let
\((\alpha_{n})\)
and
\((\beta_{n})\)
be real sequences in
\([0,1]\)
satisfying the following conditions:
-
(1)
\(0< a<\alpha_{n}\leq b< (1-k ) (1-\beta _{n} )\), \(\forall n\geq1\)
and for some constants
\(a,b\in(0,1)\);
-
(2)
\(\sum_{n=1}^{+\infty}\beta_{n}<+\infty\).
Then the sequence
\((x_{n})\)
generated from an arbitrary
\(x_{1}\in K\)
by the Ishikawa iteration method
$$\left \{ \textstyle\begin{array}{l} y_{n}= (1-\beta_{n} )x_{n}+\beta_{n}Tx_{n}, \\ x_{n+1}= (1-\alpha_{n} )x_{n}+\alpha_{n}Tx_{n}, \quad n\geq1, \end{array}\displaystyle \right . $$
converges strongly to a fixed point of
T.
The mentioned results are probably neither the most general, nor the more recent, but certainly they represent very well some of the different modifications of the original Mann approximation method, made to get strong convergence.
We would like to point out that the differences with the original method are remarkable. So it is quite surprising that recently, in [1] there was obtained a strong convergence method for nonexpansive mappings that is ‘almost’ the Mann method (the difference is given only by a smaller and smaller amount). In [1] was proved the convergence of this method only for nonexpansive mappings.
Theorem 1.6
(Hussain, Marino et al. [1], 2015)
Let
H
be a Hilbert space and
\(T:H\rightarrow H\)
a nonexpansive mapping. Let
\((\alpha_{n})\), \((\mu_{n})\)
be sequences in
\((0,1]\)
such that
-
\(\lim_{n\to\infty}\alpha_{n}=0\);
-
\(\sum_{n=1}^{+\infty}\alpha_{n}\mu_{n}=+\infty\);
-
\(\vert \mu_{n+1}-\mu_{n}\vert =o(\mu_{n})\);
-
\(\vert \alpha_{n+1}-\alpha_{n}\vert =o(\alpha_{n}\mu_{n})\).
Then the sequence
\((x_{n})\)
generated by
$$ x_{n+1}=\alpha_{n}x_{n}+ (1-\alpha_{n} )Tx_{n}-\alpha _{n}\mu_{n}x_{n} $$
strongly converges to a point
\(x^{*}\in \operatorname{Fix}(T)\)
with minimum norm
$$ \bigl\Vert x^{*}\bigr\Vert =\min_{x\in \operatorname{Fix}(T)}\Vert x \Vert . $$
We would like to emphasize that:
-
(1)
In general, the mapping T cannot be defined on a closed convex subset C of H, since \(x_{n+1}\) is not a convex combination of two elements in C. However, since we can write
$$ x_{n+1}=\alpha_{n} (1-\mu_{n} )x_{n}+ (1-\alpha _{n} )Tx_{n}, $$
then \(x_{n+1}\) is meaning full if \(T:C\rightarrow C\) is a self-mapping defined on a cone C, that is, a particular convex set, closed with respect to linear combinations with positive coefficients.
-
(2)
The proof of Theorem 1.6 is easy using the properties of nonexpansive mappings and cannot be adjusted to the strict pseudo-contractive mappings. The purpose of the present paper is to show that the result is true also for strict pseudo-contractions. The proof uses completely different techniques, as well as the assumptions on coefficients. For all we know, this is the algorithm most similar to the original iterative Mann’s method (and the one most easy to implement), providing strong convergence.
-
(3)
Our techniques can also be used to clarify the proofs of main results in [12] and [13].