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., [1356913]). 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 [21011]. 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, μ1(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=0c 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}k0,n0 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

0 < cn < 1, n N0 (2.2)

and

0 < lim ncn = 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)

3. MAIN RESULTS

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}k0 (0, 1) be a sequence such that limkbk = 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 + d2)] < h < 1 (3.1)

is strongly convergent. Then it converges to a random fixed point of T .

Proof. Since 0 < b + d2 < 14, clearly 34(1 (b + d2)) < 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 = δd 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 + d2)] < 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