Bulletin of the Transilvania University of Braşov Vol 10(59), No Series III: Mathematics, Informatics, Physics, 63-76

Similar documents
DIFFERENT ITERATIVE METHODS. Nazli Karaca and Isa Yildirim

Two-Step Iteration Scheme for Nonexpansive Mappings in Banach Space

Common fixed points of two generalized asymptotically quasi-nonexpansive mappings

AN ITERATIVE METHOD FOR COMPUTING ZEROS OF OPERATORS SATISFYING AUTONOMOUS DIFFERENTIAL EQUATIONS

New w-convergence Conditions for the Newton-Kantorovich Method

CONVERGENCE THEOREMS FOR STRICTLY ASYMPTOTICALLY PSEUDOCONTRACTIVE MAPPINGS IN HILBERT SPACES. Gurucharan Singh Saluja

Convergence to Common Fixed Point for Two Asymptotically Quasi-nonexpansive Mappings in the Intermediate Sense in Banach Spaces

Journal of Computational and Applied Mathematics

CONVERGENCE OF HYBRID FIXED POINT FOR A PAIR OF NONLINEAR MAPPINGS IN BANACH SPACES

Shih-sen Chang, Yeol Je Cho, and Haiyun Zhou

Convergence theorems for a finite family. of nonspreading and nonexpansive. multivalued mappings and equilibrium. problems with application

HAIYUN ZHOU, RAVI P. AGARWAL, YEOL JE CHO, AND YONG SOO KIM

Research Article Iterative Approximation of Common Fixed Points of Two Nonself Asymptotically Nonexpansive Mappings

Research Article Strong Convergence of a Projected Gradient Method

On the Midpoint Method for Solving Generalized Equations

The Newton-Kantorovich (NK) Method

Strong Convergence of the Mann Iteration for Demicontractive Mappings

Weak and strong convergence of an explicit iteration process for an asymptotically quasi-i-nonexpansive mapping in Banach spaces

Weak and strong convergence theorems of modified SP-iterations for generalized asymptotically quasi-nonexpansive mappings

Viscosity approximation methods for the implicit midpoint rule of asymptotically nonexpansive mappings in Hilbert spaces

Convergence Rates in Regularization for Nonlinear Ill-Posed Equations Involving m-accretive Mappings in Banach Spaces

Nonlinear equations. Norms for R n. Convergence orders for iterative methods

A CHARACTERIZATION OF STRICT LOCAL MINIMIZERS OF ORDER ONE FOR STATIC MINMAX PROBLEMS IN THE PARAMETRIC CONSTRAINT CASE

ON WEAK AND STRONG CONVERGENCE THEOREMS FOR TWO NONEXPANSIVE MAPPINGS IN BANACH SPACES. Pankaj Kumar Jhade and A. S. Saluja

Convergence analysis of a one-step intermediate Newton iterative scheme

Research Article Convergence Theorems for Infinite Family of Multivalued Quasi-Nonexpansive Mappings in Uniformly Convex Banach Spaces

Viscosity approximation method for m-accretive mapping and variational inequality in Banach space

The equivalence of Picard, Mann and Ishikawa iterations dealing with quasi-contractive operators

Mathematical Programming Involving (α, ρ)-right upper-dini-derivative Functions

A New Modified Gradient-Projection Algorithm for Solution of Constrained Convex Minimization Problem in Hilbert Spaces

Constrained controllability of semilinear systems with delayed controls

ITERATIVE SCHEMES FOR APPROXIMATING SOLUTIONS OF ACCRETIVE OPERATORS IN BANACH SPACES SHOJI KAMIMURA AND WATARU TAKAHASHI. Received December 14, 1999

Iterative algorithms based on the hybrid steepest descent method for the split feasibility problem

An improved convergence theorem for the Newton method under relaxed continuity assumptions

Renormings of c 0 and the minimal displacement problem

ON THE CONVERGENCE OF MODIFIED NOOR ITERATION METHOD FOR NEARLY LIPSCHITZIAN MAPPINGS IN ARBITRARY REAL BANACH SPACES

Comparison of the Rate of Convergence of Various Iterative Methods for the Class of Weak Contractions in Banach Spaces

Fixed Points of Multivalued Quasi-nonexpansive Mappings Using a Faster Iterative Process

Research Article Convergence Theorems for Common Fixed Points of Nonself Asymptotically Quasi-Non-Expansive Mappings

EXPANDING THE CONVERGENCE DOMAIN FOR CHUN-STANICA-NETA FAMILY OF THIRD ORDER METHODS IN BANACH SPACES

Some unified algorithms for finding minimum norm fixed point of nonexpansive semigroups in Hilbert spaces

Research Article Some Krasnonsel skiĭ-mann Algorithms and the Multiple-Set Split Feasibility Problem

On nonexpansive and accretive operators in Banach spaces

On The Convergence Of Modified Noor Iteration For Nearly Lipschitzian Maps In Real Banach Spaces

Numerical Method for Solving Fuzzy Nonlinear Equations

Research Article Strong Convergence of Parallel Iterative Algorithm with Mean Errors for Two Finite Families of Ćirić Quasi-Contractive Operators

Journal of Inequalities in Pure and Applied Mathematics

Strong Convergence of Two Iterative Algorithms for a Countable Family of Nonexpansive Mappings in Hilbert Spaces

Convergence theorems for mixed type asymptotically nonexpansive mappings in the intermediate sense

Research Article Algorithms for a System of General Variational Inequalities in Banach Spaces

On a new iteration scheme for numerical reckoning fixed points of Berinde mappings with convergence analysis

STRONG CONVERGENCE OF AN IMPLICIT ITERATION PROCESS FOR ASYMPTOTICALLY NONEXPANSIVE IN THE INTERMEDIATE SENSE MAPPINGS IN BANACH SPACES

Bulletin of the Iranian Mathematical Society Vol. 39 No.6 (2013), pp

STRONG CONVERGENCE RESULTS FOR NEARLY WEAK UNIFORMLY L-LIPSCHITZIAN MAPPINGS

Functional Norms for Generalized Bakers Transformations.

A NICE PROOF OF FARKAS LEMMA

Strong convergence of multi-step iterates with errors for generalized asymptotically quasi-nonexpansive mappings

Research Article A New Iteration Process for Approximation of Common Fixed Points for Finite Families of Total Asymptotically Nonexpansive Mappings

On constraint qualifications with generalized convexity and optimality conditions

International Journal of Scientific & Engineering Research, Volume 7, Issue 12, December-2016 ISSN

Fixed points of Ćirić quasi-contractive operators in normed spaces

A Note of the Strong Convergence of the Mann Iteration for Demicontractive Mappings

Journal of Complexity. New general convergence theory for iterative processes and its applications to Newton Kantorovich type theorems

Kantorovich s Majorants Principle for Newton s Method

New Class of duality models in discrete minmax fractional programming based on second-order univexities

Research Article Cyclic Iterative Method for Strictly Pseudononspreading in Hilbert Space

Iterative Convex Optimization Algorithms; Part One: Using the Baillon Haddad Theorem

Analysis Comprehensive Exam Questions Fall F(x) = 1 x. f(t)dt. t 1 2. tf 2 (t)dt. and g(t, x) = 2 t. 2 t

STRONG CONVERGENCE THEOREMS BY A HYBRID STEEPEST DESCENT METHOD FOR COUNTABLE NONEXPANSIVE MAPPINGS IN HILBERT SPACES

arxiv: v1 [math.oc] 1 Jul 2016

SHRINKING PROJECTION METHOD FOR A SEQUENCE OF RELATIVELY QUASI-NONEXPANSIVE MULTIVALUED MAPPINGS AND EQUILIBRIUM PROBLEM IN BANACH SPACES

TWO MAPPINGS RELATED TO SEMI-INNER PRODUCTS AND THEIR APPLICATIONS IN GEOMETRY OF NORMED LINEAR SPACES. S.S. Dragomir and J.J.

An Alternative Proof of Primitivity of Indecomposable Nonnegative Matrices with a Positive Trace

Introduction to Optimization Techniques. Nonlinear Optimization in Function Spaces

A Fractional Order of Convergence Rate for Successive Methods: Examples on Integral Equations

A convergence result for an Outer Approximation Scheme

The Split Common Fixed Point Problem for Asymptotically Quasi-Nonexpansive Mappings in the Intermediate Sense

Convergence analysis of a proximal Gauss-Newton method

CONVERGENCE THEOREMS FOR MULTI-VALUED MAPPINGS. 1. Introduction

PARALLEL SUBGRADIENT METHOD FOR NONSMOOTH CONVEX OPTIMIZATION WITH A SIMPLE CONSTRAINT

Hahn-Banach extension theorem for interval-valued functions and existence of quasilinear functionals

SOME PROPERTIES ON THE CLOSED SUBSETS IN BANACH SPACES

A Viscosity Method for Solving a General System of Finite Variational Inequalities for Finite Accretive Operators

SPACES ENDOWED WITH A GRAPH AND APPLICATIONS. Mina Dinarvand. 1. Introduction

The Journal of Nonlinear Science and Applications

ON THE CONVERGENCE OF THE ISHIKAWA ITERATION IN THE CLASS OF QUASI CONTRACTIVE OPERATORS. 1. Introduction

arxiv: v1 [math.oc] 20 Sep 2016

Research Article Iterative Approximation of a Common Zero of a Countably Infinite Family of m-accretive Operators in Banach Spaces

Math 421, Homework #9 Solutions

On Almost Contraction Principle and Property (XU)

Convergence of a Third-order family of methods in Banach spaces

SOME FIXED POINT RESULTS FOR ADMISSIBLE GERAGHTY CONTRACTION TYPE MAPPINGS IN FUZZY METRIC SPACES

PROXIMAL POINT ALGORITHMS INVOLVING FIXED POINT OF NONSPREADING-TYPE MULTIVALUED MAPPINGS IN HILBERT SPACES

Introduction to Functional Analysis

WEAK CONVERGENCE OF RESOLVENTS OF MAXIMAL MONOTONE OPERATORS AND MOSCO CONVERGENCE

On the influence of center-lipschitz conditions in the convergence analysis of multi-point iterative methods

EXISTENCE AND UNIQUENESS OF SOLUTIONS FOR A SYSTEM OF FRACTIONAL DIFFERENTIAL EQUATIONS 1. Yong Zhou. Abstract

On the split equality common fixed point problem for quasi-nonexpansive multi-valued mappings in Banach spaces

Selçuk Demir WS 2017 Functional Analysis Homework Sheet

l(y j ) = 0 for all y j (1)

Transcription:

Bulletin of the Transilvania University of Braşov Vol 1(59), No. 2-217 Series III: Mathematics, Informatics, Physics, 63-76 A CONVERGENCE ANALYSIS OF THREE-STEP NEWTON-LIKE METHOD UNDER WEAK CONDITIONS IN BANACH SPACES Nazli KARACA 1 and Isa YILDIRIM 2 Abstract In this paper, we present a local and semi-local convergence analysis for three-step Newton-like method in order to approximate a solution of nonlinear equations in a Banach space. The convergence ball and error estimates are given for these methods. Also, we give some numerical examples for this study. Our results are generalizations of the analogous ones recently proved by Sahu et al. [3]. 2 Mathematics Subject Classification: 47H1, 49M15, 65K1. Key words: Newton-like method, iterative methods, Fréchet differentiable, nonlinear equations. 1 Introduction Throughout this paper, N will denote the set of all positive integers and B(X, Y ) will designate the space of all bounded linear operators from X to Y. Also, for given any x X and r >, B r [x] = {y X : y x r} and B r (x) = {y X : y x < r}. One of the most important problems in analysis is the solution of nonlinear equation F (x) =. (1) in a Banach space X, where F is a Fréchet differentiable operator on some open convex subset C of X with values in another Banach space Y. To solve these equations we can use different iterative methods. One of them is the Newton method defined by x n+1 = x n [ F (x n ) ] 1 F (xn ), n N, (2) 1 Corresponding author, Faculty of Sciences, Ataturk University, TURKEY, e-mail: nazli.kadioglu@atauni.edu.tr 2 Faculty of Sciences, Ataturk University, TURKEY, e-mail: isayildirim@atauni.edu.tr

64 Nazli Karaca and Isa Yildirim where x is an initial point, F (x) denotes the Fréchet derivative of F at the point x C. Argyros [1], Dennis [2] and Rheinboldt [6] considered the following modified Newton method to avoid the inverse of derivative which is required at each step in Newton method (2), x n+1 = x n [ F (x ) ] 1 F (xn ), n N. (3) There are two types of the convergence analysis of iterative methods, semilocal and local convergence analysis. The semi-local convergence analysis is, based on the information around an initial point while the local one is, based on the information around a solution. In 212, Sahu et al. [3] introduced the S-iteration process of Newton-like type for finding the solution of operator equation (1) as follows: Let x X nad α (, 1). The sequence {x n+1 } is defined by; x n+1 = z n [F (x )] 1 F (z n ) z n = (1 α)x n + αy n, y n = x n [F (x )] 1 F (x n ), n N. Moreover, he showed that the rate of convergence of this iterative process is faster than (3). Let x C be a solution of (1) such that [F (x )] 1 B(Y, X). For some L,, L 2 >, x C and x C, suppose that [F (x )] 1 and F satisfy the following conditions: F (x) F (x ) L x x, (5) [ F (x ) ] 1 (F (x) F (x )) x x, (6) and [ F (x ) ] 1 (F (x) F (x )) L 2 x x. (7) In 212, Sahu et al. [3] proved some theorems on the semi-local and local convergence of the iterative method (4) to solve the operator equation (1). Recently, Karaca and Yildirim [1] introduced iteration process (8) for the class of nonexpansive mapping in Banach spaces and they proved that this iteration process is faster than Picard iteration, S and normal S-iterations [7]. Let X be a normed space, C a nonempty convex subset of X and T : C C an operator. Then, for arbitrary x C x n+1 = T y n, y n = (1 α n )z n + α n T z n, z n = (1 β n )x n + β n T x n, n N where {α n } and {β n } are sequences in (, 1). (4) (8)

Local and semi-local convergence of Newton-like method 65 Now, we introduce iteration process (8) of Newton-like type in order to find the solution of operator equation (1). Let C be an open convex subset of a Banach space X. Assume that F : X Y is a Frechet differentiable operator where Y is a Banach space. Let α, β (, 1). Starting with x X and {x n+1 } is defined by: x n+1 = y n [F (x )] 1 F (y n ) y n = z n α [F (x )] 1 F (z n ) z n = x n β [F (x )] 1 F (x n ), n N, which can be written in the following compact form: x n+1 = y n [ [F (x )] 1 F (y n ) ] y n = (1 α)z n α z n [F (x )] 1 F (z n ) [ ] z n = (1 β)x n + β x n [F (x )] 1 F (x n ), n N. (9) The aim of this paper is to prove semi-local and local convergence analysis of iteration process (9). It is shown that the rate of convergence of (9) is faster than (4). Applications to numerical examples are included. Definition 1. Let C be a nonempty subset of normed space X. T : C X is called: A mapping (i) Contraction if there exists a constant L (, 1) such that T (x) T (y) L x y for all x, y C. (ii) Quasi-contraction [8] if there exists a constant L (, 1) and F (T ) = = {x C : T (x) = x} such that T (x) p L x p for all x C and p F (T ). (iii) Lipschitzian if there exists a constant L > such that T (x) T (y) L x y for all x, y C. In the sequel, we also need the following lemmas. Lemma 1. [4] Let T be a bounded linear operator on a Banach space X. Then the following are equivalent: (a) There is a bounded linear operator P on X such that P 1 exists, and P T < 1 P 1. (b) T 1 exists. Moreover, if T 1 exists, then T 1 P 1 1 1 P 1 T P 1 1 P 1 P T.

66 Nazli Karaca and Isa Yildirim Lemma 2. [5] Let X and Y be Banach spaces, C be a nonempty open convex subset of X and F : X Y be a Fréchet differentiable operator. Assume that x C is a solution of (1) such that [F (x )] 1 B(Y, X) and the operator F satisfies the conditions (7). Suppose that B r (x ) C, where r = 1 L 2. Then, for any x B r (x ), F (x ) is invertible, and the following inequality holds: ( [ F (x ) ] 1 F (x )) 1 1 1 L 2 x x. Lemma 3. [9] Let X and Y be Banach spaces, C be a nonempty open convex subset of X and F : X Y be a Fréchet differentiable operator. Then, for all x, y C, F (x) F (y) = F (y + t(x y)) (x y)dt. 2 Main results Before studying convergence analysis of (9), we will give the following theorem. Let the operators T, S α, S β : B r [x ] X be defined as follows: for all x B r [x ] and for fixed α, β (, 1), T (x) = x [ F (x ) ] 1 F (x) (1) S α (x) = x α [ F (x ) ] 1 F (x) S β (x) = x β [ F (x ) ] 1 F (x). Theorem 1. Let F be a Fréchet differentiable operator defined on an open convex subset C of a Banach space X with values in a Banach space Y. Suppose that [F (x )] 1 B(Y, X) for some x C and the operator F satisfies the conditions (5) and [F (x )] 1 F (x ) k and [F (x )] 1 l for some k, l >. Moreover assume that γ = kll < 1 2 and B r[x ] C, where r = 1 1 2γ γ k. Then, (i) The operators (1) are contractions on B r [x ] with constant δ, (1 α (1 δ)) and (1 β (1 δ)) and the operator equation (1) has a uniqe solution in B r [x ]. (ii) The operator G : B r [x ] X, G (x) = T S α S β (x) generated by (1) is a contraction on B r [x ] with constant δ (1 α (1 δ)) (1 β (1 δ)). Proof. (i) Denote by δ := lrl. This implies that δ < 1. For all x, y B r [x ], we obtain that

Local and semi-local convergence of Newton-like method 67 S β (x) S β (y) = x y β [ F (x ) ] 1 (F (x) F (y)) = β x y [ F (x ) ] 1 (F (x) F (y)) + (1 β) x y = β x y [ F (x ) ] 1 F (y + t(x y)) (x y)dt + (1 β) x y = β [ F (x ) ] [ 1 1 F (y + t(x y)) (x y)dt F (x ) (x y)dt] + (1 β) x y β [ F (x ) ] 1 1 F (y + t(x y)) (x y)dt F (x ) (x y)dt + (1 β) x y β [ F (x ) ] 1 F (y + t(x y)) (x y) F (x ) (x y) dt + (1 β) x y βl F (y + t(x y)) F (x ) x y dt + (1 β) x y βl L y + t(x y) x x y dt + (1 β) x y βlrl x y + (1 β) x y = (1 β (1 lrl )) x y = (1 β (1 δ)) x y. Since δ < 1, we get that (1 β (1 δ)) < 1 Thus, the operator S β is a contraction. Now we need to show that S β (B r [x ]) B r [x ]. For x B r [x ], we get that = S β (x) x S β (x) S β (x ) + S β (x ) x x x β [ F (x ) ] 1 (F (x) F (x )) + x β [ F (x ) ] 1 F (x ) x β x x [ F (x ) ] 1 (F (x) F (x )) + (1 β) x x + βk β [ F (x ) ] 1 F (x + t(x x )) F (x ) x x dt + (1 β) x x + βk βl L t(x x ) x x dt + (1 β) x x + βk βll x x 2 tdt + (1 β) x x + βk

68 Nazli Karaca and Isa Yildirim βlr2 L 2 r, + (1 β) r + βk which means that S β (B r [x ]) B r [x ]. Similarly, we obtain that S α (x) S α (y) (1 α (1 δ)) x y and T (x) T (y) δ x y. (11) Thus S α and T are contractions with constant (1 α (1 δ)) and δ, respectively. Also, for x B r [x ], we get that S α (x) x r and T (x) x r. This implies that S α (B r [x ]) B r [x ] and T (B r [x ]) B r [x ]. Therefore, by Banach contraction principle, S β, S α and T have a uniqe fixed point in B r [x ]. (ii) From (11) and (11), G (x) G (y) = T S α S β (x) T S α S β (y) δ S α S β (x) S α S β (y) δ (1 α (1 δ)) S β (x) S β (y) δ (1 α (1 δ)) (1 β (1 δ)) x y. Thus, the operator G is a contraction with constant δ (1 α (1 δ)) (1 β (1 δ)). Theorem 2. Let F be a Fréchet differentiable operator defined on an open convex subset C of a Banach space X with values in a Banach space Y. Suppose that [F (x )] 1 B(Y, X) for some x C and the operator F satisfies the conditions (5) and [F (x )] 1 F (x ) k and [F (x )] 1 l for some k, l >. Moreover assume that γ = kll < 1 2 and B r[x ] C, where r = 1 1 2γ γ k. Then, (i) The sequence {x n } defined by (9) is in B r [x ] and it converges strongly to x. (ii) The following inequality holds: x n+1 x λ n+1 x x, (12) where λ = δ (1 α (1 δ)) (1 β (1 δ)) and δ = lrl. Proof. (i) From Theorem 1, there is a unique solution of the equation (1). Let

Local and semi-local convergence of Newton-like method 69 x B r [x ]. Using (9), we get x n+1 x = G(x n ) G(x ) (13) = T S α S β (x n ) T S α S β (x ) Thus, x n x, as n. (ii) It follows from (13). δ S α S β (x n ) S α S β (x ) δ (1 α (1 δ)) S β (x n ) S β (x ) δ (1 α (1 δ)) (1 β (1 δ)) x n x. [δ (1 α (1 δ)) (1 β (1 δ))] n+1 x x. Remark 1. From the inequality (3.9) in Theorem 3.5 in [3] and (12) λ = δ (1 α (1 δ)) (1 β (1 δ)) < δ (1 α + αδ). (14) The inequality (14) shows that the error estimate in Theorem 2 is sharper than that of Theorem 3.5 in [3]. Our next result is as follows: Theorem 3. Let F be a Fréchet differentiable operator defined on an open convex subset C of a Banach space X with values in a Banach space Y. Let x C be a solution of (1) such that [F (x )] 1 B(Y, X). Suppose that [F (x )] 1 and F satisfy the conditions (6) and (7) with B r (x ) C and x B r (x ), where r 1 = 1 2 L 2 and r = 2L 2 +3. Moreover, assume that the operators S β, S α and T are defined by (1). Then (i) For x B r (x ), T (x) x γ x x x, (15) S α (x) x (αγ x + 1 α) x x, S β (x) x (βγ x + 1 β) x x, L where γ x = 1 2(1 rl 2 ) ( x x + 2 x x ). (ii) T, S α and S β are quasi-contraction operators on B r (x ) with constant γ, 1 (1 γ)α and 1 (1 γ)β, respectively, where γ = sup x Br(x ) {γ x }. Proof. (i) Let x B r (x ) with x x. From (1), T (x) x = x [ F (x ) ] 1 F (x) x (16) = [ F (x ) ] 1 ( (F (x) F (x )) F (x ) (x x ) ) = ([ F (x ) ] 1 F (x )) 1 [ F (x ) ] 1 ( F (tx + (1 t)x ) (x x ) F (x ) (x x ) ) dt

7 Nazli Karaca and Isa Yildirim It follows from (6), (16) and Lemma 2, T (x) x 2(1 rl 2 ) ( x x + 2 x x ) x x = γ x x x. Using the operator S α defined by (1), S α (x) x = x α [ F (x ) ] 1 F (x) x = α(x x ) α [ F (x ) ] 1 (F (x) F (x )) + (1 α)(x x ) α [ F (x ) ] 1 (F (x) F (x )) (x x ) + (1 α) x x = α ([ F (x ) ] 1 F (x )) 1 [ F (x ) ] 1 F (tx + (1 t)x ) ( (x x ) F (x ) (x x ) ) dt + (1 α) x x α ( [ F (x ) ] 1 F (x )) 1 [ F (x ) ] 1 ( F (tx + (1 t)x ) F (x ) ) x x dt + (1 α) x x Again using (6) and Lemma 2, we obtain that S α (x) x α 1 L 2 x x t(x x ) + (x x ) x x dt + (1 α) x x α 1 L 2 x x α 2(1 rl 2 ) ( x x + 2 x x ) x x + (1 α) x x = (αγ x + 1 α) x x. (t x x + x x ) x x dt + (1 α) x x Similarly, taking β instead of α, we deduce that S β (x) x (βγ x + 1 β) x x. (ii) The operators T, S α and S β are quasi-contractions. Indeed, ( ) γ = sup {γ x } = sup x x + 2 x x x B r(x ) 2(1 rl 2 ) x B r(x ) 2(1 rl 2 ) (r + 2 x x ) 3r < 2(1 rl 2 ) = 1

Local and semi-local convergence of Newton-like method 71 Since γ < 1, we get that 1 (1 γ)α < 1 and 1 (1 γ)β < 1. Finally, we will give the following theorem on the local convergence analysis for iteration process (9). Theorem 4. Let F be a Fréchet differentiable operator defined on an open convex subset C of a Banach space X with values in a Banach space Y. Let x C be a solution of (1) such that [F (x )] 1 B(Y, X). Suppose that [F (x )] 1 and F satisfy the conditions (6) and (7). Also assume that B r1 (x ) C, where r 1 = 1 L 2 and for any x B r (x 2 ), where r = 2L 2 +3. Then (i) The sequence {x n } defined by (9) is in B r (x ) and it converges strongly to the unique solution x in B r1 (x ). (ii) The following inequality holds: x n+1 x (λ ) n+1 x x (17) where λ = (αγ + 1 α)(βγ + 1 β)γ and γ = 3 2(1 rl 2 ) x x. Proof. (i) Firstly, we will show that x is unique solution of (1) in B r1 (x ). On the contrary, suppose that y is another solution of (1) in B r1 (x ). From Lemma 3, we obtain = F (x ) F (y ) = Now, we can define an operator L by L(h) = F (y + t(x y )) (x y )dt. F (y + t(x y )) hdt, for all h X. Thus, we get I [ F (x ) ] 1 1 [ L = F (x ) ] 1 (F (x ) F (y + t(x y )))dt L 2 2 x y < L 2r 1 2 = 1 2. From Lemma 1, we know that the operator L is invertible. Thus, x = y, which is a contradiction. That is, x is the unique solution of (1) in B r1 (x ). Since the S α and S β defined by (1) are operators on B r [x ], from (9), we get z = S β (x ), y = S α S β (x ) B r (x ). Also the operator V defined by (1) is an operator on B r [x ] from Theorem 3. Therefore, (9) can be written as x n+1 = T S α S β (x n ). (18)

72 Nazli Karaca and Isa Yildirim From (18), we have x n+1 x = T S α S β (x n ) x γ yn S α S β (x n ) x By using the definition of γ x, we obtain γ yn = Hence, we have γ yn (αγ zn + 1 α) S β (x n ) x γ yn (αγ zn + 1 α)(βγ zn + 1 β) x n x. 2(1 rl 2 ) ( S αs β (x n ) x + 2 x x ) 2(1 rl 2 ) [(αγ z n + 1 α) S β (x n ) x + 2 x x ] 2(1 rl 2 ) [ S β(x n ) x + 2 x x ] 2(1 rl 2 ) [(βγ z n + 1 β) x n x + 2 x x ] 2(1 rl 2 ) [ x x + 2 x x ] 3 2(1 rl 2 ) x x = γ. x n+1 x [(αγ + 1 α)(βγ + 1 β)γ ] n+1 x x. (19) which implies that x n x as n. (ii) From (19), we obtain that desired error estimate. 3 Numerical Examples In this section, we will give two numerical examples in order to support our main results. The first example shows numerically that our method (9) is faster than the modified Newton method (3) and SIP of Newton-like (4). Example 1. Let X = R, C = (1, 4) and F : C R an operator defined by F (x) = x 2 4, x C. Then F is Frechet differentiable and its Frechet derivative F (x) at any point x C is given by F (x) = 2x. For x = 3, we have [F (x )] 1 = 1 6. Set k =.83333333333, l =.16666666667 and L = 2, we have γ = kll < 1 2 and [ F (x ) ] 1 l, [ F (x ) ] 1 F (x ) k, F (x) F (x ) L x x.

Local and semi-local convergence of Newton-like method 73 Because all the conditions of Theorem 2 are satisfied, the sequence {x n } generated by (9) is in B r [x ] and it converges to a unique x B r [x ]. From the following table and figure, we see that the new method (9) is faster than the modified Newton method (3) and SIP of Newton-like (4). n modified Newton method SIP of Newton-like our method 1 3. 3. 3. 2 2.166666666666667 2.137731481481481 2.985135333972 3 2.5925925925926 2.28722838184148 2.139913466623 4 2.165436698674 2.62992634182 2.263514436 5 2.5468743484692 2.139579933914 2.34966616767 6 2.181792996914 2.39979239996 2.451743763 7 2.65425844776 2.68874489454 2.6692359848 8 2.2174752485 2.1534958953 2.991457861 9 2.67242391272 2.34178132 2.146882583 1 2.22413376834 2.755793962 2.2176382 11 2.747141885 2.167954156 2.322376 12 2.249337992 2.37323143 2.477594 13 2.83111631 2.829432 2.7755 14 2.27673762 2.1843118 2.1482 15 2.92234575 2.49582 2.1553 16 2.3744857 2.9118 2.23 17 2.1248285 2.2226 2.34 18 2.341695 2.4495 2.5 19 2.1138699 2.999 2.1 2 2.379566 2.222 2. The following example shows the convergence of (9) in infinite dimensional space. Example 2. Let X = C[, 1 4 ] be the space of real-valued continuous functions defined on the interval [, 1 4 ] with norm x = max t 1 x(t). Consider the 4 integral equation of Fredholm type F (x) =, where F (x)(s) = cos 2πs π 2 s sin 2πtx 2 (t)dt, with s [, 1 4 ] and x C[, 1 4 ]. It is easy to find the Frèchet derivative of F as F (x) h(s) = h(s) + π Now, we have F (x ) = cos 2πs π 2 1 + π max 2 1 + x 2 8 s [, 1 4 ] s sin 2πtx(t)h(t)dt, h X. s sin 2πtx 2 (t)dt s sin 2πtdt x 2

74 Nazli Karaca and Isa Yildirim and Moreover, we get I F (x ) = F (x) F (x ) = π s sin 2πtx (t)dt π max s sin 2πtdt x s [, 1 4 ] x 4. π s sin 2πtx(t)dt π s sin 2πtx (t)dt π s sin 2πt (x(t) x (t)) dt π max s sin 2πtdt x x s [, 1 4 ] x x 4 and if x 4 < 1, then by Lemma 1, we obtain Thus, we get [ F (x ) ] 1 4 4 x. [ F (x ) ] 1 F (x ) 8 + x 2 8 4 x. For the initial point x (s) = 1 2, we obtain [ F (x ) ] 1 l = 1.142857 [ F (x ) ] 1 F (x ) k = 1.178571 L =.25. Hence, γ = kll =.336734 < 1 2. So the conditions of Theorem 2 are satisfied. Therefore, the sequence {x n } generated by (9) is in B r [x ] and it converges to a uniqe solution x B r [x ] of the integral equation. Acknowledgement. We thank the reviewers for their constructive comments, which helped us improve the manuscript. This work was supported by Ataturk University Rectorship under The Scientific and Research Project of Ataturk University, Project No.: 216/153.

Local and semi-local convergence of Newton-like method 75 References [1] Argyros, I. K., Computational Theory of Iterative Methods, Series: Studies in Computational Mathematics, vol. 15, Elsevier Publ. Comp., New York, 27. [2] Dennis, J. E., On the Kantorovich hypothesis for Newton s method, SIAM Journal on Numerical Analysis, 6 (1969), 493-57. [3] Sahu, D. R., Singh, K. K., and Singh, V. K., Some Newton-like methods with sharper error estimates for solving operator equations in Banach spaces, Fixed Point Theory and Applications, 1 (212), 1-2. [4] Rall, L. B., Computational Solution of Nonlinear Operator Equations, John Wiley and Sons, New York, 1969. [5] Ren, H., and Argyros, I. K., On convergence of the modified Newtons method under Hölder continuous Fréchet derivative, Applied Mathematics and Computation, 213 (29), 44-448. [6] Rheinboldt, W. C., A Unified Convergence Theory for a Class of Iterative Processes, SIAM Journal on Numerical Analysis, 5 (1968), 42-63. [7] Sahu, D. R., Applications of the S-iteration process to constrained minimization problems and split feasibility problems, Fixed Point Theory, 12 (211), 187-24. [8] Scherzer, O., Convergence criteria of iterative methos based on Landweber iteration for solving nonlinear problems, Journal of Mathematical Analysis and its Applications, 194 (1995), 911-933. [9] Suhubi, E. S., Functional Analysis, Kluwer Academic Publishers, London, 23. [1] Karaca, N. and Yildirim, I., Approximating fixed points of nonexpansive mappings by a faster iteration process, Journal of Advanced Mathematical Studies, 8(215), 257-264.

76 Nazli Karaca and Isa Yildirim