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volume 4, issue 2, article 34, 2003.

Received 28 January, 2003;

accepted 29 March, 2003.

Communicated by:A. Fiorenza

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Journal of Inequalities in Pure and Applied Mathematics

RATE OF CONVERGENCE OF SUMMATION-INTEGRAL TYPE OPERATORS WITH DERIVATIVES OF BOUNDED VARIATION

VIJAY GUPTA, VIPIN VASISHTHA AND M. K. GUPTA

School of Applied Sciences,

Netaji Subhas Institute of Technology, Sector 3 Dwarka, New Delhi-110045, India.

E-Mail:[email protected] Department of Mathematics, Hindu College,

Moradabad -244001, India.

Department of Mathematics, Ch. Charan Singh University, Meerut-255004,

India.

E-Mail:[email protected]

c

2000Victoria University ISSN (electronic): 1443-5756 013-03

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Rate of Convergence of Summation-Integral Type Operators with Derivatives Of

Bounded Variation

Vijay Gupta, Vipin Vasishtha and M.K. Gupta

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J. Ineq. Pure and Appl. Math. 4(2) Art. 34, 2003

Abstract

In the present paper, we estimate the rate of convergence of the recently introduced generalized sequence of linear positive operatorsG_n,c(f, x)with derivatives of bounded variation.

2000 Mathematics Subject Classification:41A25, 41A30.

Key words: Linear positive operators, Bounded variation, Total variation, Rate of convergence.

1. Introduction

LetDB_γ(0,∞),(γ ≥0)be the class of all locally integrable functions defined on(0,∞), satisfying the growth condition|f(t)| ≤M t^γ, M >0andf⁰ ∈BV on every finite subinterval of[0,∞). Then for a functionf ∈ DB_γ(0,∞)we consider the generalized family of linear positive operators which includes some well known operators as special cases. The generalized sequence of operators is defined by

(1.1) G_n,c(f, x) = n

∞

X

k=1

p_n,k(x;c) Z ∞

0

p_n+c,k−1(t;c)f(t)dt

+pn,0(x;c)f(0), x∈[0,∞) wherep_n,k(x;c) = (−1)^{k x}_k!^kφ^(k)_n,c(x),

(i) φ_n,c(x) = e^−nxforc= 0,

(ii) φ_n,c(x) = (1 +cx)^−n/cforc∈N, and

φ_n,c _n∈

N be a sequence of functions defined on an interval[0, b], b > 0 having the following properties for everyn∈N,k ∈N₀ :

(i) φ_n,c ∈C^∞([a, b]) ; (ii) φ_n,c(0) = 1;

(iii) φ_n,cis completely monotone(−1)^kφ^(k)_n,c(x)≥0;

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(iv) There exists an integercsuch thatφ^(k+1)_n,c =−nφ^(k)_n+c,c, n >max{0,−c}. Remark 1.1. We may remark here that the functions φ_n,c have various appli- cations in different fields, like potential theory, probability theory, physics and numerical analysis. A collection of most interesting properties of such functions can be found in [10, Ch. 4].

It is easily verified that the operators (1.1) are linear positive operators. Also G_n,c(1, x) = 1.The generalized new sequenceG_n,cwas recently introduced by Srivastava and Gupta [9].

For c = 0 and φ_n,c(x) = e^−nx the operators G_n,c reduce to the Phillips operators (see e.g. [7], [8]), which are defined by

(1.2) G_n,0(f, x) =n

∞

X

k=1

p_n,k(x; 0) Z ∞

0

pn,k−1(t; 0)f(t)dt

+e^−nxf(0), x∈[0,∞), wherep_n,k(x; 0) = ^e^−nx_k! (nx)^k.

Forc = 1andφ_n,c(x) = (1 +cx)^−n/cthe operators Gn,c reduce to the new sequence of summation integral type operators [6], which are defined by (1.3) G_n,1(f, x) = n

∞

X

k=1

p_n,k(x; 1) Z ∞

0

p_n+1,k−1(t; 1)f(t)dt

+ (1 +x)⁻ⁿf(0), x∈[0,∞),

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where

pn,k(x; 1) =

n+k−1 k

x^k(1 +x)^n−k.

Remark 1.2. It may be noted that forc= 1, we get the Baskakov basis functions p_n,k(x; 1)which are closely related to the well known Meyer-Konig and Zeller basis functionsm_n,k(t) = ^n+k−1_k

t^k(1−t)ⁿ, t∈[0,1]because by replacing the variablet with _1+x^x in the above MKZ basis functions we get the Baskakov basis functions. Zeng [11] obtained the exact bound for the Meyer Konig Zeller basis functions. Very recently Gupta et al. [6] used the bound of Zeng [11] and estimated the rate of convergence for the operatorsGn,1(f, x)on functions of bounded variation.

The operators (1.3) are slightly modified form of the operators introduced by Agarwal and Thamer [1], which are defined by

(1.4) G^∗_n,1(f, t) = (n−1)

∞

X

k=1

p_n,k(x; 1) Z ∞

0

p_n,k−1(t; 1)f(t)dt

+ (1 +x)⁻ⁿf(0), x∈[0,∞), wherep_n,k(x; 1)is as defined by (1.3) above.

Recently Gupta [5] estimated the rate of approximation for the sequence (1.4) for bounded variation functions. Although the operators defined by (1.3) and (1.4) above are almost the same, but the main advantage to consider the operators in the form (1.3) rather than the form (1.4) is that some approximation properties become simpler in the analysis for the form (1.3) in comparison to the form (1.4). The rate of approximation with derivatives of bounded variation

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has been studied by several researchers. Bojanic and Cheng ([2], [3]) estimated the rate of convergence with derivatives of bounded variation for Bernstein and Hermite-Fejer polynomials by using different methods.

Alternatively we may rewrite the operators (1.1) as

(1.5) G_n,c(f, x) =

Z ∞ 0

K_n(x, t;c)f(t)dt, where

K_n(x, t;c) =n

∞

X

k=1

p_n,k(x;c)pn+c,k−1(t;c) +p_n,0(x;c)p_n,0(t;c)δ(t),

δ(t)being the Dirac delta function. Also let

(1.6) β_n(x, t;c) =

Z t 0

K_n(x, s;c)ds then

β_n(x,∞;c) = Z ∞

0

K_n(x, s;c)ds = 1.

In the present paper we extend the results of [4] and [6] and study the rate of convergence by means of the decomposition technique of functions with derivatives of bounded variation. More precisely the functions having derivatives of bounded variation on every finite subinterval on the interval [0,∞)be defined as

f(x) =f(0) + Z x

0

ψ(t)dt, 0< a≤x≤b,

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whereψis a function of bounded variation on[a, b]andcis a constant.

We denote the auxiliary functionf_x, by

f_x(t) =











f(t)−f(x⁻), 0≤t < x;

0, t =x;

f(t)−f(x⁺), x < t <∞.

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2. Auxiliary Results

In this section we give certain results, which are necessary to prove the main result.

Lemma 2.1. [9]. Let the functionµ_n,m(x), m∈N⁰,be defined as µ_n,m(x;c) = n

∞

X

k=1

pn,k(x;c) Z ∞

0

pn+c,k−1(t;c) (t−x)^mdt+(−x)^mpn,0(x;c).

Then

µ_n,0(x;c) = 1, µ_n,1(x;c) = cx (n−c),

µ_n,2(x;c) = x(1 +cx) (2n−c) + (1 + 3cx)cx (n−c) (n−2c) , and there holds the recurrence relation

[n−c(m+ 1)]µ_n,m+1(x;c)

=x(1 +cx)

µ⁽¹⁾_n,m(x;c) + 2mµ_n,m−1(x;c)

+ [m(1 + 2cx) +cx]µ_n,m(x;c). Consequently for eachx∈[0,∞),we have from this recurrence relation that

µ_n,m(x;c) = O n^−[(m+1)/2]

.

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Remark 2.1. In particular, given any number λ > 2and x > 0from Lemma 2.1, we have forc∈N⁰ andnsufficiently large

(2.1) G_n,c (t−x)², x

≡µ_n,2(x;c)≤ λx(1 +cx)

n .

Remark 2.2. It is also noted from (2.1), that

(2.2) Gn,c(|t−x|, x)≤ Gn,c (t−x)², x¹₂

≤

pλx(1 +cx)

√n . Lemma 2.2. Letx ∈(0,∞)andK_n(x, t)be defined by (1.5). Then forλ > 2 and fornsufficiently large, we have

(i) β_n(x, y;c) = Ry

0 K_n(x, t;c)dt≤ ^λx(1+cx)_n(x−y)2 ,0≤y < x, (ii) 1−β_n(x, z;c) =R∞

z Kn(x, t;c)dt ≤ ^λx(1+cx)_n(z−x)2 , x < z <∞.

Proof. First, we prove (i). In view of (2.1), we have Z y

0

Kn(x, t;c)dt≤ Z y

0

(x−t)²

(x−y)²Kn(x, t;c)dt≤(x−y)⁻²µ_n,2(x;c)

≤ λx(1 +cx) n(x−y)² . The proof of (ii) is similar.

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3. Main Result

In this section we prove the following main theorem.

Theorem 3.1. Let f ∈ DBγ(0,∞), γ > 0, andx ∈ (0,∞). Then forλ > 2 and fornsufficiently large, we have

|G_n,c(f, x)−f(x)| ≤ λ(1 +cx) n





 [^√ⁿ] X

k=1 x+^x_k

_

x−^x_k

((f⁰)_x) + x

√n

x+^√^x_n

_

x−^√^x

n

((f⁰)_x)







+λ(1 +cx) n

f(2x)−f(x)−xf⁰ x⁺

+|f(x)|

+

pλx(1 +cx)

√n M2^γO n^−γ/2 +

f⁰ x⁺

+1 2

pλx(1 +cx)

√n

f⁰ x⁺

−f⁰ x⁻

+ cx

2 (n−c)

f⁰ x⁺

+f⁰ x⁻ , whereWb

a(f_x)denotes the total variation off_xon[a, b].

Proof. We have

G_n,c(f, x)−f(x) = Z ∞

0

K_n(x, t;c) (f(t)−f(x))dt

= Z ∞

0

Z t x

Kn(x, t;c)f⁰(u)du

dt.

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Using the identity f⁰(u) = 1

2

f⁰ x⁺

+f⁰ x⁻ + (f⁰)_x(u) + 1

2

f⁰ x⁺

−f⁰ x⁻

sgn (u−x) +

f⁰(x)− 1 2

f⁰ x⁺

+f⁰ x⁻

χ_x(u), it is easily verified that

Z ∞ 0

Z t x

f⁰(x)− 1 2

f⁰ x⁺

+f⁰ x⁻

χ_x(u)du

K(x, t;c)dt= 0.

Also Z ∞

0

Z t x

1 2

f⁰ x⁺

−f⁰ x⁻

sgn (u−x)du

K_n(x, t;c)dt

= 1 2

f⁰ x⁺

−f⁰ x⁻

G_n,c(|t−x|, x) and

Z ∞ 0

Z t x

1 2

f⁰ x⁺

+f⁰ x⁻ du

K(x, t;c)dt

= 1 2

f⁰ x⁺

+f⁰ x⁻

G_n,c((t−x), x).

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Thus we have

|G_n,c(f, x)−f(x)|

(3.1)

≤

Z ∞ x

Z t x

(f⁰)_x(u)du

K_n(x, t;c)dt

− Z x

0

Z t x

(f⁰)_x(u)du

K_n(x, t;c)dt +1

2

f⁰ x⁺

−f⁰ x⁻

G_n,c(|t−x|, x) +1

2

f⁰ x⁺

+f⁰ x⁻

G_n,c((t−x), x)

=|A_n(f, x;c) +B_n(f, x;c)|

+1 2

f⁰ x⁺

−f⁰ x⁻

G_n,c(|t−x|, x) +1

2

f⁰ x⁺

+f⁰ x⁻

G_n,c((t−x), x).

To complete the proof of the theorem it is sufficient to estimate the termsA_n(f, x;c) and B_n(f, x;c). Applying integration by parts, using Lemma 2.2 and taking y =x−x/√

n, we have

|B_n(f, x;c)|=

Z x 0

Z t x

(f⁰)_x(u)du

dt(β_n(x, t;c)) ,

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Z x 0

β_n(x, t;c) (f⁰)_x(t)dt

≤ Z y

0

+ Z x

y

|(f⁰)_x(t)| |β_n(x, t;c)|dt

≤ λx(1 +cx) n

Z y 0

x

_

t

((f⁰)_x) 1

(x−t)²dt+ Z x

y x

_

t

((f⁰)_x)dt

≤ λx(1 +cx) n

Z y 0

x

_

t

((f⁰)_x) 1

(x−t)²dt+ x

√n

x

_

x−^√^x

n

((f⁰)_x).

Letu=x/(x−t). Then we have λx(1 +cx)

n

Z y 0

x

_

t

((f⁰)_x) 1

(x−t)²dt= λx(1 +cx) n

Z

√n

1 x

_

x−^x

u

((f⁰)_x)du

≤ λ(1 +cx) n

[^√ⁿ] X

k=1 x

_

x−^x_u

((f⁰)_x).

Thus

(3.2) |B_n(f, x;c)| ≤ λ(1 +cx) n

[^√ⁿ] X

k=1 x

_

x−^x_u

((f⁰)_x) + x

√n

x

_

x−^√^x

n

((f⁰)_x).

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On the other hand, we have

|A_n(f, x;c)|=

Z ∞ x

Z t x

(f⁰)_x(u)du

K_n(x, t;c)dt (3.3)

=

Z ∞ 2x

Z t x

(f⁰)_x(u)du

K_n(x, t;c)dt +

Z 2x x

Z t x

(f⁰)_x(u)du

dt(1−β_n(x, t;c))

≤

Z ∞ 2x

(f(t)−f(x))K_n(x, t;c)dt +

f⁰ x⁺

Z ∞ 2x

(t−x)K_n(x, t;c)dt +

Z 2x x

(f⁰)_x(u)du

|1−β_n(x,2x;c)|

+ Z 2x

x

|(f⁰)_x(t)| |1−β_n(x, t;c)|dt

≤ M x

Z ∞ 2x

K_n(x, t;c)t^γ|t−x|dt + |f(x)|

x²

Z ∞ 2x

K_n(x, t;c) (t−x)²dt +

f⁰ x⁺

Z ∞ 2x

K_n(x, t;c)|t−x|dt + λ(1 +cx)

nx

f(2x)−f(x)−xf⁰ x⁺

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+ λ(1 +cx) n

[^√ⁿ] X

k=1 x+^x_k

_

x

((f⁰)_x) + x

√n

x+^√^x_n

_

x

((f⁰)_x). Next applying Hölder’s inequality, and Lemma 2.1, we proceed as follows for the estimation of the first two terms in the right hand side of (3.3):

M x

Z ∞ 2x

Kn(x, t;c)t^γ|t−x|dt+ |f(x)|

x²

Z ∞ 2x

Kn(x, t;c) (t−x)²dt (3.4)

≤ M x

Z ∞ 2x

K_n(x, t;c)t^2γdt

¹₂ Z ∞ 0

K_n(x, t;c) (t−x)²dt ¹₂

+|f(x)|

x²

Z ∞ 2x

K_n(x, t;c) (t−x)²dt

≤M2^γO n^−γ/2

pλx(1 +cx)

√n +|f(x)|λ(1 +cx) nx . Also the third term of the right side of (3.3) is estimated as

f⁰ x⁺

Z ∞ 2x

K_n(x, t;c)|t−x|dt

≤

f⁰ x⁺

Z ∞ 0

K_n(x, t;c)|t−x|dt

≤

f⁰ x⁺

Z ∞ 0

K_n(x, t;c) (t−x)²dt

¹₂ Z ∞ 0

K_n(x, t;c)dt ¹₂

=

f⁰ x⁺

pλx(1 +cx)

√n .

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Combining the estimates (3.1) – (3.4), we get the desired result.

This completes the proof of Theorem3.1.

Remark 3.1. For negative values ofc, the operatorsG_n,cmay be defined in dif- ferent ways. Here we consider one such example, whenc=−1thenφ_n,c(x) = (1−x)ⁿ,the operator reduces to

Gn,−1(f, x) = n

n

X

k=1

p_n,k(x;−1) Z 1

0

pn−1,k−1(t;−1)f(t)dt + (1−x)ⁿf(0), x∈[0,1], where

p_n,k(x;−1) =n k

x^k(1−x)^n−k.

The rate of convergence for the operators Gn−1(f, x)is analogous so we omit the details.

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References

[1] P.N. AGARWAL AND K.J. THAMAR, Approximation of unbounded function by a new sequence of linear positive operators, J. Math. Anal.

Appl., 225 (1998), 660–672.

[2] R. BOJANI ´CANDF. CHENG, Rate of convergence of Bernstein polyno- mials for functions with derivatives of bounded variation, J. Math. Anal Appl., 141 (1989), 136–151.

[3] R. BOJANI ´CANDF. CHENG, Rate of convergence of Hermite Fejer poly- nomials for functions with derivatives of bounded variation, Acta Math.

Hungar., 59 (1992), 91–102.

[4] V. GUPTA AND G.S. SRIVASTAVA, On the rate of convergence of Phillips operators for functions of bounded variation, Commentation Math., XXXVI (1996), 123–130.

[5] V. GUPTA, Rate of approximation by new sequence of linear positive op- erators, Comput. Math. Appl., 45(12) (2003), 1895–1904.

[6] V. GUPTA, M.K. GUPTA ANDV. VASISHTHA, An estimate on the rate of convergence of Bezier type summation integral operators, Kyungpook Math. J., (to appear).

[7] C.P. MAY, On Phillips operators, J. Approx. Theory, 20 (1977), 315–322.

[8] R.S. PHILLIPS, An inversion formula for semi groups of linear operators, Ann. Math., 59 (1954), 352–356.

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[9] H.M. SRIVASTAVA AND V. GUPTA, A certain family of summation in- tegral type operators, Math. Comput. Modelling, 37 (2003), 1307–1315.

[10] D.V. WIDDER, The Laplace Transform, Princeton University Press, Princeton, 1941.

[11] X.M. ZENG, Bounds for Bernstein basis functions and Meyer Konig and Zeller basis functions, J. Math. Anal. Appl., 219 (1998), 364–376.

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