Lobachevskii Journal of Mathematics
http://ljm.ksu.ru
Vol. 14, 2004, 33–38
© M. Ghulam
Ghulam Mustafa
A DOUBLE-SEQUENCE RANDOM ITERATION PROCESS
FOR RANDOM FIXED POINTS OF CONTRACTIVE
TYPE RANDOM OPERATORS
(submitted by A. Lapin)
ABSTRACT. In this paper, we introduce the concept of a Mann-type
double-sequence random iteration scheme and show that if it is strongly
convergent then it converges to a random fixed point of continuous
contractive type random operators. The iteration is a random version of
double-sequence iteration introduced by Moore (Comput. Math. Appl.
43(2002), 1585-1589).
________________
2000 Mathematical Subject Classification. 54H25, 47H10.
Key words and phrases. Double-sequence iteration, Mann iteration, Strong
convergence, Random Fixed point, Contractive mapping.
|
1. INTRODUCTION
Several iteration processes have been established for the constructive
approximation of solutions to several classes of (nonlinear) operator equations
and many important convergence results have been obtained in terms of these
iterative processes( cf. e.g., [1, 3, 5, 6, 9, 13]). Most of these convergence results
require that the operator is of the strong (accretive or pseudocontractive)
type whereas a few of them do not need the strong type property. Moreover,
Mann-type and Ishikawa iteration processes play a key role in most of these
convergence results. Most recently, a new Mann-type iteration process called
Mann-type double-sequence iteration process was introduced be Moore
[8].
On the other hand, random fixed point theory has attracted more and more
in recent years since the article by Bharucha-Reid [7] come out in 1976. We
note some recent works on random fixed points in [2, 10, 11]. In order to
construct iterations for finding fixed points of random operators defined on
linear spaces, random Ishikawa iteration scheme was introduced in
[4].
In this paper, we will introduce the concept of a Mann-type double-sequence
random iteration scheme. We will show that if this random iteration scheme
converges strongly then it converges to a random fixed point of continuous
contractive type random operators defined in the context of a separable
Hilbert space.
2. PRELIMINARIES
NOTATIONS: In this paper X
is a separable Hilbert space, (Ω,
Σ) is measurable
space (i.e,
Σ is a sigma-algebra
of subsets of Ω),
C is a nonempty
subset of X,
2C is the family of
all subsets of C
and N0
is the set of all nonnegative integers.
CONCEPTS: A mapping μ : Ω → 2C
is called measurable if for any open subset
U of
C,
μ−1(U) = {w ∈ Ω : μ(w) ∩ U≠∅}∈ Σ. A mapping
T : Ω × C → C is called a random
operator if for any x ∈ C,
T (.,x) is measurable. A
measurable mapping f : Ω → C
is called a random fixed point of random operator
T : Ω × C → C if for
every w ∈ Ω,
f(w) = T(w,f(w)). A random operator
T : Ω × C → C is said to be
continuous if, for fixed w ∈ Ω,
T (w,.) is
continuous.
DOUBLE SEQUENCE.[8] Let E
be a normed linear space. By a double sequence in
E is meant
functions fk,n : Ω → E
defined by fk,n(w) := wk,n ∈ E,
∀
k, n ∈ N0. The double
sequence {wk,n} is said to
converge strongly to w∗
if for each ε > 0, there
exist integers K,N > 0,
such that wk,n − w∗ < ε,
∀
k ≥ K,
n ≥ N. If
∀
k, r ≥ K,
n, s ≥ N, we
have wk,r − wn,s < ε,
then the double sequence is said to be Cauchy.
MANN ITERATION SCHEME.[9] Let
L be a linear space,
T : L → L be a mapping
and x0 ∈ L. Then
the sequence {xn}
defined iteratively by:
xn+1 = (1 − cn)xn + cnTxn, n ∈ N0
where0 ≤ cn < 1and ∑
n=0∞c
n < ∞
is called the Mann iteration scheme.
bf DOUBLE-SEQUENCE RANDOM MANN ITERATION SCHEME. Suppose
that C
be a nonempty convex subset of a separable Hilbert space
X,
T k : Ω × C → C
be random operators. The double sequence of functions
{fk,n}k≥0,n≥0
generated from an arbitrary measurable function
f0,0 : Ω → C
defined by
fk,n+1(w) = (1 − cn)fk,n(w) + cnTk(w,fk,n(w)),
w ∈ Ω,k,n ∈ N0
| (2.1) |
where
and
0 < lim n→∞cn = h < 1,
| (2.3) |
is called double-sequence random mann iteration scheme.
Since C is convex
clearly, fk,n is a
mapping from Ω → C
for all k,n ∈ N0.
CONTRACTIVE INEQUALITY A. Let
C
be a nonempty convex subset of a Hilbert space
X. A
mapping S : C → C
is said to satisfy contractive inequality A if for all
x, y ∈ C,
Sx − Sy2 ≤ a x − y2 + b y − Sy2(1 + x − Sx2)
+d
2 x − Sy2(1 + x − Sx2 + y − Sx2),
wherea,b,d > 0,k ≥ 0,b + d
2 < 1
4.
CONTRACTIVE INEQUALITY B. Let
C
be a nonempty convex subset of a separable Hilbert space
X. The random
operator T : Ω × C → C
is said to satisfy contractive inequality B if for all
x, y ∈ C,
T(w,x) − T(w,y)2
≤ a x − y2 + b y − T(w,y) 2 1 + x − T(w,x2)
+(d
2) x − T(w,y) 2(1 + x − T(w,x) 2 + y − T(w,x) 2),
| (2.4) |
wherea,b,d > 0,k ≥ 0,b + d
2 < 1
4. (2.5)
Theorem 3.1. Let X be
a separable Hilbert space, C
be a nonempty closed convex subset of
X,
T : Ω × C → C
be a continuous random operator such that for all
w ∈ Ω,
T satisfies contractive
inequality B. Let {bk}k≥0 ⊂ (0, 1) be
a sequence such that limk→∞bk = 1.
For an arbitrary but fixed t ∈ C,
and for each k ≥ 0,
define Tk : Ω × C → C
by Tk(w,x) = (1 − bk)t + bkT(w,x).
Suppose that the double-sequence random Mann iteration scheme
satisfying
3
4[1 − (b + d∕2)] < h < 1 (3.1)
is strongly convergent. Then it converges to a random fixed point of
T .
Proof. Since 0 < b + d∕2 < 1∕4, clearly
3∕4(1 − (b + d∕2)) < 1. So the positive number
h satisfying (3.1) exists.
Let {fk,n(w)} be constructed by
(2.1)-(2.3) with h satisfying
(3.1) and {fk,n(w)} be strongly
convergent. Then for all w ∈ Ω,
if for each fixed k,
fk,n(w) → fk∗(w) as
n →∞ and
then fk∗(w) → f(w)
as k →∞,
then
fk,n(w) → f(w)ask,n →∞.
| (3.2) |
Since C is closed, it
follows that f is a
mapping from Ω → C.
Since C
is a subset of a separable Hilbert space
X, for any continuous
random operator F and
any measurable function g
from Ω → C,
G(w) = F(w,g(w)) is
also a measurable function [12]. It thus follows from (2.1)-(2.3) that
{fk,n}
is a sequence of measurable functions. Hence,
f : Ω → C,
being the limit of a sequence of measurable functions, is also measurable. For
w ∈ Ω, from
(2.1) and parallelogram law we have
f(w) − Tk(w,f(w))2
= f(w) − fk,n+1(w) + fk,n+1(w) − Tk(w,f(w)) 2
≤ 2 f(w) − fk,n+1(w) 2 + 2 f
k,n+1(w) − Tk(w,f(w)) 2
= 2 f(w) − fk,n+1(w) 2
+2 (1 − cn)fk,n(w) + cnTk(w,fk,n(w)) − Tk(w,f(w)) 2
≤ 2 f(w) − fk,n+1(w) 2 + 4(1 − c
n)2 f
k,n(w) − Tk(w,f(w)) 2 +
4cn2 T
k(w,fk,n(w)) − Tk(w,f(w)) 2.
Therefore by (2.4) we obtain
f(w) − Tk(w,f(w))2 ≤ β + 4c
n2(γ + α), (3.3)
where
α = δ d
2 fk,n(w) − Tk(w,f(w)) 2,
δ = 1 + fk,n(w) − Tk(w,fk,n(w)) 2 + f(w) − T
k(w,fk,n(w)) 2,
β = 2 f(w) − fk,n+1(w) 2 + 4(1 − c
n)2 f
k,n(w) − Tk(w,f(w)) 2,
γ = a fk,n(w) − f(w) 2
+ b f(w) − Tk(w,f(w)) 2 1 + f
k,n(w) − Tk(w,fk,n(w)) 2 .
Since
fk,n(w) − Tk(w,fk,n(w))2 = fk,n(w) − fk,n+1(w) 2
cn2 , (3.4)
It follows that
f(w) − Tk(w,fk,n(w))2 ≤ 2 f(w) − f
k,n(w) 2 (3.5)
+2 fk,n(w) − Tk(w,fk,n(w)) 2
= 2 f(w) − fk,n(w) 2 + 2
cn2 fk,n(w) − fk,n+1(w) 2. (3.6)
Using (3.4) and (3.5) in (3.3), we have, for all
w ∈ Ω,
f(w) − Tk(w,f(w))2 ≤ β∗ + 4c
n2(γ∗ + α∗),
where
α∗ = δ∗d
2 fk,n(w) − Tk(w,f(w)) 2,
δ∗ = 1 + 2 f(w) − f
k,n(w) 2 + 2
cn2 + 1
cn2 fk,n(w) − fk,n+1(w) 2,
β∗ = 2 f(w) − f
k,n+1(w) 2 + 4(1 − c
n)2 f
k,n(w) − Tk(w,f(w)) 2,
γ∗ = a f
k,n(w) − f(w) 2
+b f(w) − Tk(w,f(w)) 2 1 + fk,n(w) − fk,n+1(w) 2
cn2 .
Letting k,n →∞, using (3.2),
(2.3) and the fact that Tk
are continuous random operators, we obtain, for
w ∈ Ω,
f(w) − T(w,f(w))2 ≤ 4(1 − h)2 f(w) − T(w,f(w)) 2
+4h2 b f(w) − T(w,f(w)) 2 + d
2 f(w) − T(w,f(w)) 2
= 4(1 − h)2 + 4h2 b + d
2 f(w) − (w,f(w)) 2.
From (2.5) and (3.1) we have
(1 − h)2 + h2(b + d
2) < 1
4.
Therefore, for all w ∈ Ω
and k ≥ 0, we
have f(w) = T(w,f(w)).
This completes the proof.
Following is the immediate consequence of theorem 3.1.
Corollary 3.1. Let X be a
Hilbert space, C be a nonempty
closed convex subset of X,
S : C → C be a
function satisfying contractive inequality A. Suppose that the Mann iteration
scheme satisfying
3
4[1 − (b + d∕2)] < h < 1
is convergent. Then it converges to a fixed point of
T .
References
[1] R. E. Bruck. The iteration solution of the equation
y ∈ x + Tx
for a monotone operator T
in Hilbert spaces. Bull, Amer. Math. Soc. 79 (1973), 1259-1262
[2] Beg and Shahzad N. Random fixed point theorems for nonexpansive and
contractive type random opeartors on Banach spaces. J. Appl. Math. Stoc. Anal.
1994, 7: 569-580.
[3] C. E. Chidume and C. Moore. Fixed point iteration for pseudocontractive maps.
Proc. Amer. Math. Soc. 127 (1999), 1163-1170
[4] B. S. Choudhury. Convergence of a random iteration scheme to a random fixed
point. J. Appl. Math. Stoc. Anal. 8 (1995), 139-142
[5] J. A. Park. Mann-iteration process for the fixed point of strictly pseudocontractive
mappings in some Banach spaces. J. Korean Soc. 31(1994), 333-337
[6] S. Ishikawa. Fixed points by a new iteration method.. Proc. Amer. Math. Soc. 44
(1974), 147-150
[7] Bharucha-Reid A T. Fixed point theorems in probabilistic analysis. Bull. Amer.
Math. Soc. 1976, 82: 641-645
[8] C. Moore. A double-sequence iteration process for fixed points of continuous
pseudoconstructions. Comput. Math. Appl. 43 (2002), 1585-1589
[9] W. R. Mann. Mean value methods in iteration. Proc. Amer. Math. Soc. 4 (1953),
506-510
[10] Adrian Constantin. A random fixed point theorem for multifunctions. Stoch.
Anal. &
Appl. 12(1994), 65-73
[11] G. Mustafa. Some random coincidence and random fixed point theorems for
non-self hybrid contractions. Canadian Math. Bull. (2003), in press.
[12] C. J. Himmelberg. Measurable relations. Fund. Math. 87(1975), 53-72
[13] B. E. Rhoades. Fixed point iterations for certain nonlinear mappings. J. Math.
Anal. Appl. 183(1994), 118-120
DEPARTMENT OF MATHEMATICS,
UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA,
HEFEI, ANHUI 230026, P.R.CHINA
E-mail address: mustafa_rakib@yahoo.com
Received July 8, 2003