Posts by Ion Păvăloiu

Abstract

Authors

Ioannis K. Argyros
(Cameron University, USA)

Emil Cătinaş

Emil Cătinaş

Ion Păvăloiu

Ion Păvăloiu

Keywords

chord/secant method; semilocal convergence; r-convergence order.

Cite this paper as:

I. Argyros, E. Cătinaş, I. Păvăloiu, Improving the rate of convergence of some Newton-like methods for the solution of nonlinear equations containing a nondifferentiable term, Rev. Anal. Numér. Théor. Approx., 27 (1998) no. 2, pp. 191-202.

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Google Scholar citations

[1] K. Argyros, On the solution of equations with nondifferentiable operators and the Ptak error estimates, BIT, 30 (1990), pp. 752-754.

[2] I. K. Argyros, On the solution of nonlinear equations with a nondifferentiable term, Rev. Anal. Numer. Theor. Approx., 22 (1993) 2, pp. 125-135.

[3] I. K. Argyros, On some iterative methods for solving nonlinear equations with a nondifferentiable term of order between 1.618… and 1.839. (submitted to this joumal).

[4] I. K. Arglros, and F. Szidarovszky, The Theory and Application of lteration Method, CRC Press, Inc., Boca Raton, Florida, 1993.

[5] E. Cătinaș, On some iterative methods for solving nonlinear equations, Rev. Anal. Numer. Theor. Approx., 23, I (1994), pp. 47-53.

[6] G. Goldner, and M. Balazs, Remarks on divided differences and method of chords, Rev. Anal. Numer. Theor. Approx., 3, I (1974), pp. 19-30.

[7] L. V. Kantorovich, The method of successive approximation for functional equations, Acta Math. 71 (1939), pp. 63-97.

[8] J. M. Ortega and W. C. Rheinboldt, Iterative Solution of Nonlinear Equations in Several Variables, Academic Press, New York, 1970.

[9] I. Păvăloiu, Sur une generalisation de la methode de Steffensen, Rev. Anal. Numer. Theor. Approx., 21, 1 (1992), pp. 59-65.

[10] I. Păvăloiu, A convergence theorem concerning the chord methods, Rev. Anal. Numer. Theor. Approx., 22, 1 (1993), pp. 83-85.

[11] F. A, Potra, On an iterative algorithm of order 1.839 . . . for solving nonlinear equations, Numer. Funct. Anal. Optimiz. 7, I (1984-1985), pp. 75-106.

[12] T. Yamamoto and X. Chen, Convergence domains of certain iterative methods for solving nonlinear equations, Numer. Funct. Anal. Optimiz. 10, 1 and 2 (1989), pp.37-48.

Paper (preprint) in HTML form

Improving the rate of convergence of some Newton-Like methods for the solution of nonlinear equations containing A nondifferentiable term

Improving the rate of convergence of some Newton-Like methods for the solution of nonlinear equations containing A nondifferentiable term

Ioannis K. Argyros, Emil Cătinaş, Ion Păvăloiu

s⁢u⁢b⁢s⁢o⁢l: AMS (MOS) Subject Classification: 65J15, 65G99, 47H15, 49D15.

1 Introduction

In this study we are concerned with the problem of approximating a locally unique solution x∗ of a nonlinear equation

F⁢(x)+G⁢(x)=0 (1)

where F,G are defined on a closed convex subset D of a Banach space E1 with values in a Banach space E2. The operator F is Fréchet-differentiable on D whereas G is only continuous there.

We use the Newton-Like method given by

xn+1=xn+An−1⁢(F⁢(xn)+G⁢(xn))(n≥0) (2)

to generate a sequence {xn}⁢(n≥0) converging to x∗. Here An is a linear operator approximating F′⁢(xn)⁢(n≥0). Sufficient conditions for the convergence of (2) to x∗ have given by several authors ([1], [2], [3], [4], [5],[7], [8], [11] and [12]). Recently, Cătinaş in [5] has used (2) for

An=F′⁢(xn)+[xn−1,xn;G](n≥1), (3)

where [x,y;G] denotes a divided difference of order one of G on D for x,y∈E1. This way Cătinaş has managed to show that the order of convergence denoted by λlies in [1+52,2]. Cătinaş has also showed that iteration (2) is faster than iterations appearing in [1],[2], [4], [5], [7], [8],[11] and [12] for choices of An other than the one given by (3).

In [3] we used (2) for

An=[xn,xn−1;F]+[xn−2,xn;F]−[xn−2,xn−1;F]+[xn−1,xn;G](n≥0). (4)

We showed that λ∈[1+52,1.839⁢…]. Sufficient conditions were also provided under which our error bounds are sharper than all previous ones (in particular those in [5]). We also note that our method is cheaper to use than that in [5].

In this study we have made a further attempt to improve the rate of convergence of iteration (2) by choosing An appropriately. Sufficient convergence conditions as well as an error analysis have been provided.

Finally we show that our error bounds are smaller than all earlier ones ([1], [2], [3], [4], [5], [7], [8], [9], [10], [11] and[12]).

2 Convergence analysis

We need the following definitons on divided differences [4], [9], [10].

Definition 1

An operator denoted by [x0,y0;H] belonging to the space L⁢(D,E2),D⊆E1 (the Banach space of bounded linear operators from E1 to E2 is called the first order divided difference of the operator H:D→E2 at the points x0,y0∈D if the following hold:

(a)
[x0,y0;H]⁢(y0−x0)=H⁢(y0)−H⁢(x0),f⁢o⁢r⁢x0≠y0. (5)
(b)

If H is Fréchet-differentiable at x0∈D, then [x0,x0;H]=H′⁢(x0).

Definition 2

An operator denoted by [x0,y0,z0;H] belonging to the space L⁢(D,L⁢(D,E2)) is called the second order divided difference of the operator H:D⊆E1→E2 at the points x0,y0,z0∈D if the following hold:

(a)
[x0,y0,z0;H]⁢(z0−x0)=[y0,z0;H]−[x0,y0;H]. (6)
(b)

If H is twice Fréchet-differentiable at x0∈D, then

[x0,x0,x0;H]=12⁢H′′⁢(x0).

We can prove the following semilocal result concerning the convergence of iteration (2).

Theorem 3

Assume that there exist points x0,x1∈D and nonnegative real numbers R, ε and m such that:

(a)

U⁢(x1,R)={x∈E1|‖x−x1‖≤R}⊆D;

(b)

the operators F,G have divided differences of order one denoted by [x,y;F] and [x,y;G] respectively for all x,y∈U⁢(x1,R);

(c)

the linear operators An are invertible for all n≥0 and

‖An−1⁢Bn‖≤pn⁢‖xn−1−xn−2‖+q⁢‖xn−xn−1‖=εn⁢(n≥1),

for some nonnegative sequences {pn}, {qn}⁢(n≥1) with

pn+qn≤ε⁢(n≥1),

where

Bn=[xn−1,xn;F]+[xn−1,xn;G]−An−1⁢(n≥1),
(d)

the points x0,x1 satisfy ‖x1−x0‖≤m;

(e)

the following conditions hold:

‖x2−x1‖≤‖x1−x2‖, (7)

with x2 given by (2) for n=1,

r=m⁢ε<1, (8)
R≥mr⁢∑k=1∞rk, (9)
rk=rsk,(k≥0), (10)

where {sk} is the Fibonacci’s sequence

s0=s1=1,sk+1=sk+sk−1,(k≥0). (11)

Then

(i)

the sequence {xn}⁢(n≥0), generated by (2) is well defined, remains in U⁢(x0,R) and converges to a solution x∗∈U⁢(x0,R) of the equation F⁢(x)+G⁢(x)=0;

(ii)

the following a priori error estimated hold

‖x∗−xn‖≤m⁢tnr⁢(1−tnℓ−1),(n≥1), (12)

where

tn=rℓ5,(n≥1)and ⁢ℓ=1+52; (13)
(iii)

moreover, if there exists a nonnegative number g such that

‖An−1⁢Bn∗‖≤g<1,(n≥1), (14)

where

Bn∗=[y∗,xn;F]+[y∗,xn;G]−An,(n≥1), (15)

with y∗ satisfying

F⁢(y∗)+G⁢(y∗)=0and ⁢y∗∈U⁢(x0,R),

then

x∗=y∗.

Proof. We shall show by induction that, for all n≥2

xn∈U⁢(x1,R), (16)
‖xn−xn−1‖≤‖xn−1−xn−2‖ (17)

and

‖xn−xn−1‖≤mr⁢rn−1. (18)

For n=2 relations (16)-(18) follow from hypothses (d) and (e). Suppose relations (16)-(18) hold for n=2,3,…⁢k, where k≥2. Since xk,xk−1∈U⁢(x1,R) and Ak is invertible, via (2) we can compute xk+1. Using (2), we can obtain the approximation

F⁢(xk)+G⁢(xk) =F⁢(xk)+G⁢(xk)−F⁢(xk−1)−G⁢(xk−1)−Ak−1⁢(xk−xk−1)= (19)
=([xk−1,xk;F]+[xk−1,xk;G]−Ak−1)⁢(xk−xk−1)=
=Bk⁢(xk−xk−1)⁢by (16))

By (2), (7??), (8???) and (19) we get

‖xk+1−xk‖≤εk⁢‖xk−xk−1‖≤ε⁢‖xk−1−xk−2‖⋅‖xk−xk−1‖. (20)

From the induction hypothese, (20) give on the one hand, that

‖xn+1−xk‖≤εr⁢rk−2⁢m⁢‖xk−xk−1‖=rk−2⁢‖xk−xk−1‖<‖xk−xk−1‖,

that is, (17) for n=k+1, and, on the other hand

‖xk+1−xk‖≤rk−2⁢‖xk−xk−1‖≤rk−2⁢rk−1⁢mr=mr⁢rk,

which shows (18) for n=k+1.

We must also show that xk+1∈U⁢(x1,R). Indeed, from the induction hypotheses and the triangle inequality we get

‖xk+1−x1‖≤‖x2−x1‖+‖x3−x2‖+…+‖xk+1−xk‖≤mr⁢∑j=1krk<R.

We must show that sequence {xn}⁢(n≥0) is Cauchy. We have that the Fibonacci’s sequence {sk}⁢(k≥0) given by (11) can also be written as

sk=15⁢[(1+52)k+1−(1−52)]≥15⁢(1+52)⁢κ=ℓk5⁢(k≥1).

Therefore, for any k≥1,j≥1 we get

‖xk+j−xk‖ ≤‖xk+1−xk‖+‖xk+2−xk+1‖+…+‖xk+j−xk+j−1‖≤
≤mr⁢∑j=kk+j−1ri≤mr⁢∑i=kk+j−1rℓl5.

Moreover, by Bernoulli’s inequality we get

‖xk+j−xk‖ ≤mr⁢rℓk5⁢[1+rℓk+1−ℓk5+rℓk+2−ℓ5+…+rℓk+j−1−ℓk5]≤ (21)
≤mr⁢rℓk5⁢[1+rℓl⁢(ℓ−1)5+rℓk⁢[1+2⁢(ℓ−1)−1]5+…+r[1+(j−1)⁢(ℓ−1)−1]5]
=mr⁢rℓk5⁢1−rvk⁢ℓ−15⁢j1−rℓl⁢(ℓ−1)5⁢(k≥1).

By (8)and (21) it follows that the sequence {xn}⁢(n≥0) is Caucchy in a Banch space E1, and so it converges to some point x∗∈U⁢(x1,R) (since U⁢(x1,R) is a closed set). By letting n→∞ in (2), we obtain F⁢(x∗)+G⁢(x∗)=0; that is, x∗∈U⁢(x1,R) is a solution of equation (1). Moreover, by letting j→∞ in (21) we obtain (12).

Furhermore, to show that x∗ is the unique solution of equation (1) in U⁢(x1,R), let us assume that y∗∈U⁢(x1,R) is a solution of equation (1) too.

xk+1−y∗ =xk−y∗−Xk−1⁢(F⁢(xk)+G⁢(xk))= (22)
=−Ak−1⁢[F⁢(xk)−F⁢(y∗)+G⁢(xk)−G⁢y∗−Ak⁢(xk−y∗)]=
=−Ak−1⁢Bk∗⁢(xk−y∗),

and hypothesis (14), we get

‖xk+1−y∗‖ ≤‖Ak−1⁢Bk∗‖⁢‖xk−y∗‖≤ (23)
≤g⁢‖xk−y∗‖≤…≤gk⁢‖x1−y∗‖≤gk⁢R.

Since 0≤g<1, by letting k→∞ in (23) we get limk→∞xk=y∗. But we have also showed that limk→∞xk=x∗. Hence, we deduce x∗=y∗.

That completes the proof of the Theorem.  

Remark 4

Let us consider some special choices for the linear operators An. Set

An=[xn,yn;F]+[hn,zn;F]−[hn,zn−1;F]+[vn,xn;G]⁢(n≥0), (24)

where the sequences {yn}, {zn}, {vn}, {hn}∈U⁢(x1,R)⁢(n≥0) are given by

yn =xn+αn⁢(xn−1−xn),zn=zn−1⁢βn⁢(xn−1−xn),z−1=x−1∈U⁢(x1,R),
vn =xn+yn⁢(xn−1−xn)⁢(n≥0),

for some linear operator sequence {αn}, {βn} and {γn}⁢(n≥0) with γn≠0 (n≥0). Assume that there exist nonnegative numbers a,b,c and a real sequence {an} (n≥0) such that for all x,y,v,w,z∈U⁢(x1,R)

‖A0−1⁢([x,y;F]−[v,w;F])‖≤v⁢(‖x−v‖+‖y−w‖) (25)
‖An−1⁢A0‖≤an≤a⁢(n≥0), (26)

and

‖An−1⁢[x,y,z;G]‖≤c, (27)

where [x,y,z;G] is the divided difference of order two of G on U⁢(x1,R). Then form the approximation

G⁢(xn)−G⁢(xn−1)−[vn−1,xn−1;G]⁢(xn−xn−1)=
=([xn−1;G]−[vn−1,xn−1;G])⁢(xn−xn−1)=
=[vn−1,xn−1,xn;G]⁢(xn⁢vn−1)⁢(xn−xn−1),

hypotheses (25), (26) and (27) we get

‖A0−1⁢(G⁢(xn)−G⁢(xn−1)−[vn−1,xn−1;G]⁢(xn−xn−1))‖≤
≤c⁢‖xn−vn−1‖⁢‖xn−xn−1‖≤
≤c⁢(‖xn−vn−1‖+‖γn‖⁢‖xn−1−xn−2‖)⁢‖xn−xn−1‖⁢(n≥0).

The sequence {an}⁢(n≥1) can be computed as follows. Let us assume that there exist c¯≥0 such that

‖A0−1⁢([x,y;G]−[v0,x0;G])‖≤c¯⁢(‖x−v0‖+‖y−x0‖), (28)

for all x,y,v0,x0∈U⁢(x1,R). Then from the approximation

A0−1(An−A0)=A0−1{[xn,yn;F]+[hn,zn;G]−[hn,zn−1;G]+
+[vn,xn;G]−[x0,y0;F]−[h0,z0;F]+[h0,z−1;F]−[v0,x0;G]},

we can get as before

‖A0−1⁢(An−A0)‖≤a¯n⁢(n≥1),

where

a¯n =b⁢(‖xn−x0‖+‖yn−y0‖+2⁢‖hn−h0‖+‖zn−z0‖+‖zn−1−z−1‖)+
+c¯⁢(‖vn−x0‖+‖xn−x0‖)⁢(n≥1),

and a¯n<1 if the function a⁢(r)=(11⁢b+2⁢c¯)⁢r+(b+2⁢c¯)⁢m satisfies

a⁢(R)<1, (29)

since

a¯n≤a⁢(R)(n≥1).

It follows from the Banach lemma on invertible operators that An−1 exists (n≥1) and

‖An−1⁢A0‖≤(1−a¯n)−1.

We can now set an=(1−a¯n)⁢(n≥1) and a=(1−(R))−1. Moreover, from the approximation

F⁢(xn)−F⁢(xn−1)−
−([xn−1,yn−1;F]+[hn−1,zn−1;F]−[hn−1,zn−1;F])⁢(xn−xn−1)
=([xn−1,xn;F]−[xn−1,yn−1;F]−[xn−1,zn−1;F])+[xn−1,zn−2;F])(xn−xn−1),

hypothese (25), (26), and (27) and (28) we also get

||A0−1{F(xn)−F(xn−1)− (30)
−([xn−1,yn−1:F]+[hn−1,zn−1;F]−[hn−1,zn−2;F])(xn−xn−1)}||
≤b⁢(‖xn−yn−1‖+‖zn−1−zn−2‖)⁢‖xn−xn−1‖≤
≤b⁢(‖xn−xn−1‖+‖αn−1+βn−1‖⁢‖xn−2−xn−1‖)⁢‖xn−xn−1‖⁢(n≥1).

Define the sequences {dn}, {δn} (n≥1) by

dn=(b+c)anand δn=an(c||γn||+b(||αn||+||βn||)](n≥0). (31)
‖xn+1−xn‖≤(dn⁢‖xn−xn−1‖+δn⁢‖xn−1−xn−2‖)⁢‖xn−xn−1‖⁢(n≥1). (32)

Hence we can set

pn=δnand ⁢dn=qn(n≥0). (33)

We can impose additional conditions on the sequences {αn}, {βn} and {γn} (n≥0)⁢t⁢h⁢a⁢t will guarantee that {yn}, {zn}, {vn}∈U⁢(x1,R). Let us assume that there exist nonnegative numbers α, β, and γ such that

‖αn‖≤a,‖βn‖≤βand ⁢‖γn‖≤γ⁢(n≥0).

Then, from the approximations

yn−x1 =(xn−x1)+αn⁢(xn−1−xn)
vn−x1 =(xn−x1)+γn⁢(xn−1−xn)
zn−x1 =(xn−1−x1)+βn⁢(xn−1−xn),

we can have

‖xn−x1‖+‖αn‖⁢‖xn−1−xn‖≤mr⁢∑i=1n−1ri+m⁢αr⁢rn−1, (34)
‖vn−x1‖+‖γn‖⁢‖xn−1−xn‖≤mr⁢∑i=1n−1ri+m⁢γr⁢rn−1, (35)

and

‖zn−x1‖≤‖z−1−x1‖+β⁢∑i=0n−1‖xi−xi−1‖≤‖z−1−x1‖+β⁢mr⁢∑i=0n−1ri. (36)

Hence yn,vn,zn∈U⁢(x1,R)⁢(n≥0) if the right hand sider of the last three inequalities are respectively bounded above by R.

Finally, the uniqueness of the solution x∗ can be extended in the ball U⁢(x1,R1) for R1≥R provided that the following inequality holds

g=(5⁢(b+c¯)⁢R+(b+c)⁢R1+2⁢m⁢c¯)⁢(1−a⁢(R))−1<1. (37)

Indeed, as in (22) we get

Bn∗ =([y∗,xn;F]−[xn,yn;F])+([y∗,xn;G]−[x0,v0;G])+
+([x0,v0;G]−[vn,xn;G])+([hn,zn−1;F]−[hn,zn;F]).

Composing both sides of the above approximation by A0−1, we easily deduce that A0−1⁢Bk∗ (in norm) is bounded above by the expression in the bracket of inequality (37). Hence, as in the proff of the Theorem, we deduce x∗=y∗.

Concluding, we note that we have showed: if hypotheses (c) of the Theorem are replaced by (24), (25), (26), (27), (28) and (37), then the conclusions of the Theorem hold in the ball U⁢(x1,R1).

Remark 5

Iteration (2) reduces to (4) considered in [5] if the linear operators {An}⁢(n≥0) are given by (24) for αn=0, γn=I, βn=0, zn=0 (n≥0).

Using the notation introduced in [5], we can set

εn1=M⁢K⁢‖xn−1−xn−2‖+M⁢(ℓ2+K)⁢‖xn−xn−1‖⁢(n≥2). (38)

Hence our error bounds (12) will be smaller than those in [5] , say if (see also (33)).

pn≤M⁢Kand ⁢qn≤(M⁢ℓ2+K)⁢(n≥2) (39)

and our initial error bounds ‖x1−x0‖ are not greater than those in [5]. The choice of pn,qn given by (33) shows that conditions (39) will be true if an,αn,βn and γn⁢(n≥0) are ”small” enough.

Remark 6

Moreover, iteration (2) reduces to (1) considered in [11] if the linear operators {An}⁢(n≥0) are given by (24) for G=0, αn=I, βn=I, zn=xn and hn=xn−2⁢(n≥0). Using the notation introduced in [11] we can set

εn2=q0⁢‖xn−3−xn−1‖⁢‖xn−2−xn−1‖+p0⁢‖xn−xn−1‖⁢(n≥1). (40)

Hence our error bounds (12) will be smaller in this case, say if

pn≤‖xn−3−xn−1‖⁢and ⁢qn≤p0(n≥1). (41)

Observations similar to those made at the end of Remark 2 can now follows.

Remark 7

Furthermore, iteration (2) reduces to (5) considered in [3] if the linear operators {An}⁢(n≥0) are given by (24) for

αn=I,βn=0,γn=I,zn=xn,hn=xn−2⁢(n≥0).

Using the notation introduced in [3], we can set

εn3=(c4+c2⁢‖xn−3−xn−1‖)⁢‖xn−1−xn−2‖+(x1+c4)⁢‖xn−xn−1‖⁢(n≥1). (42)

Hence our bounds will be smaller in this case say if

pn≤c4+c2⁢‖xn−3−xn−1‖⁢and ⁢qn≤c1+c4(n≥1). (43)
Remark 8

Our results extend to included perturbed Newton-like methods of the form

xn+1=xn−An−1⁢(F⁢(xn)+G⁢(xn))−wn(n≥0). (44)

The points {wn}⁢(n≥0) are determined in such a way that interation {xn} (n≥0) converges to a solution x∗ of equation (1). The import;ance of studying perturbed Newton-like methods comes from the fact that many commonly used variants of Newton’s method can be considered procedures of this type. Indeed, approximation (44) characterizes any iterative process in which corrections are taken as approximate solutions of Newton equations. We also note that if, for example, an equation on the real is solved, F⁢(xn)>0⁢(n≥0), and A⁢(xn)⁢(n≥0) overestimates the derivative xn−An−1⁢F⁢(xn), is always larger than the corresponding Newton iterate. In such cases, a positive wn⁢(n≥0) correction term is appropriate. Let us assume that there exists a real sequence {u}⁢(n≥0) such that

‖An⁢(wn)−An⁢(wn−1)‖≤un(n≥1). (45)

Moreover, there exist real sequences {ℓn}, {mn} (n≥0) such that

un≤(ℓn⁢‖xn−1−xn−2‖+mn⁢‖xn−xn−1‖)⁢‖xn−xn−1‖(n≥1). (46)

Set

p¯n=pn+ℓnand ⁢q¯n=qn+mn(n≥1).

Furthermore, assume that sequence {wn}⁢(n≥0) is null. Finally, assume that the rest of the hypotheses of the Theorem are true with p¯n,q¯n replacing pn, qn (n≥1), respectively. Then it can easily be seen that the conclusions of the Theorem will hold for the perturbed Newton-Like method generated by (44). Indeed, for example, approximation (19) will read

F⁢(xk)+G⁢(x)+Ak⁢(wk)=[Bk+(Ak⁢(wk)−Ak−1⁢(wk−1))]⁢(xk−xk−1)(n≥1)

and by using the proof of the theorem, (45) and (46) we can arrive at (20). The rest is left to the motivated reader.

Remark 9

The selection of the points {yn}, {zn}, {vn} (n≥0) can be generalized to include a wider range of problems. Let T1, T2, T3:D⊆E1→E2 begiven operators. Define for all n≥0 yn=T1⁢(xn), zn−zn−1=T2⁢(xn), z−1=x−1∈U⁢(x1,R)⊆D and vn=T3⁢(xn). For this choice of T1,T2and T3 iteration (2)becomes a Steffensen-like method ([8], [9] and [10]). Moreover, operators T1, T2 and T3 must be chosen so that estimte (7??) be true. See how this is done, for example, in Remark 1.

References

  • [1] I. K. Argyros, On the solution of equations with nondifferentiable operators and the Ptak error estimates, BIT, 30 (1990), 752-754.
  • [2] I. K. Argyros, On the solution of nonlinear equations with a nodifferentiable term, Rev. Anal. Numér. Théorie Approximation 22, 2(1993), 125-135.
  • [3] I. K. Argyros, On some iterative methods for solving nonlinear equations with a nondifferentiable term of order between 1.618…and 1.839…(sumitted to this journal).
  • [4] I. K. Argyros, and F. Szidarovszky, The Theory and Application of Iteration Methods, C.R.C., Press, Inc., Boca Raton, Florida, 1993.
  • [5] E. Cătinaş, On some iterative method for solving nonlinear equations, Rev. Anal. Numér. Theorie Approximation 23, 1 (1994), 47-53.
  • [6] G. Goldner, and M. Balazs, Remarks on divided differences and method of chords, Rev. Anal. Numér Theorie Approximation 3, 1 (1974), 19-30.
  • [7] L. V. Kantorovich, The method of succesive approximation for functional equations, Acta. Math. 71 (1939), 63-97.
  • [8] J. M. Ortega and W. C. Rheinboldt, Iterative Solution of Nonlinear Equations in Several Variables, Academic Press, New York, 1970.
  • [9] I. Păvăloiu, Sur une généralisation de la méthod de Steffensen, Rev. Anal. Numér. Theorie Approximation 21, 1 (1972), 59-65.
  • [10] I. Păvăloiu, A convergence theorem concerning the chord methods, Rev. Anal. Numér. Theorie Approximation 22, 1 (1993), 83-85.
  • [11] F. A. Potra, On an iterative algorithm of order 1.839…for solving nonlinear equations, Numer. Funct. Anal. Optimiz. 7, 1 (1984-1985), 75-106.
  • [12] T. Yamamoto and X. Chen, Convergence domains of certain iterative methods for solving nonlinear equations, Numer. Funct. Anal. Optimix. 10, 1 and 2 (1989), 37-48.

Received August 10, 1996      Ioannis K. Argyros

Cameron University

Department of Mathematics

Lawton, OK 73505, U.S.A.

Emil Cătinaş and Ion Păvăloiu

Institutul de Calcul ”Tiberiu Popoviciu”

Str. Republicii Nr.37

C.P. 68, 3400 Cluj-Napoca, Romania

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