Approximation results on Dunkl generalization of Phillips operators via q calculus

R E S E A R C H

Open Access

Approximation results on Dunkl

generalization of Phillips operators via

q

-calculus

Md. Nasiruzzaman

_{, Aiman Mukheimer}

_{and M. Mursaleen}

*_{Correspondence:} [email protected]

3_{Department of Mathematics,}

Aligarh Muslim University, Aligarh, India

Full list of author information is available at the end of the article

Abstract

The main purpose of this paper is to constructq-Phillips operators generated by Dunkl generalization. We prove several results of Korovkin type and estimate the order of convergence in terms of several moduli of continuity.

MSC: Primary 41A25; 41A36; secondary 33C45

Keywords: Szász operator; Generating functions; Dunkl analogue; Generalization of exponential function; Modulus of continuity; Weighted modulus of continuity

1 Introduction and auxiliary results

In 1950, Szász [27] defined the following operators for a continuous function f ∈C[0, ∞):

Sn(f;x) =e–nx

∞

k=0

(nx)k k! f

k n

, (1.1)

provided that the series is convergent. In [26], Sucu approximated the Szász-operators de-fined by (1.1) by Dunkl generalization with an exponential function (see [24]). Forυ> –1₂, Cheikh et al. [6] studied q-Hermite type polynomials and gave definitions of q-Dunkl analogues of exponential functions and recursion formula as follows:

eυ,q(x) =

∞

n=0

xn

γυ,q(n)

, x∈[0,∞), Eυ,q(x) =

∞

n=0

qn(n2–1)_xn

γυ,q(n)

, x∈[0,∞), (1.2)

γυ,q(n+ 1) =

1 –q2υθn+1+n+1

1 –q

γυ,q(n), n∈N, (1.3)

θn=

⎧ ⎨ ⎩

0 ifn∈2N,

1 ifn∈2N+ 1. (1.4)

Theq-integer [n]qandq-factorial [n]q!, respectively, are defined by

[n]q=

⎧ ⎪ ⎪ ⎨ ⎪ ⎪ ⎩

1–qn

1–q forq= 1,n∈N,

1 forq= 1,

0 forn= 0,

[n]q! =

⎧ ⎨ ⎩

1 forn= 0,

n

k=1[k]q forn∈N.

(1.5)

Theq-calculus appeared as a new area in approximation theory and has a lot of applica-tions in different mathematical areas and physics such as number theory, combinatorics, orthogonal polynomials, basic hypergeometric functions, quantum theory, mechanics, and the theory of relativity (see [13–15]).

Içöz [11] generalized the Dunkl–Szász operators defined by (1.1) viaq-integers as fol-lows:

Dn,q(f;x) =

1 eυ,q([n]qx)

∞

k=0

([n]qx)k

γυ,q(k)

f

1 –q2υθ_k+k

1 –qn

, (1.6)

forυ>1

2,x≥0, 0 <q< 1 andf∈C[0,∞).

Recent improvements of Szász type operators generated by exponential function via Dunkl generalization are given in [1–3,12,16–18,20,23,25,28].

The main purpose of this article is to construct theq-Phillips operators generated by Dunkl generalization viaq-calculus. For more details on the approximation of classical Phillips operators via Dunkl type version, we refer to the recent article [21]. We obtain a Korovkin type result, as well as local and weighted approximations. We also study con-vergence properties by using the modulus of continuity and investigate the rate of conver-gence for functions belonging to the Lipschitz class. For further details and more infor-mation on approxiinfor-mation, we refer to [9,10,19].

For everyf ∈Cζ[0,∞) ={f ∈C[0,∞) :f(t) =O(tζ),t→ ∞}andx∈[0,∞),ζ >n,n∈ N∪ {0},υ≥–1₂, we define

P∗

n,q(f;x) =

[n]q

eυ,q([n]qx)

∞

k=0

Qυ_n,q(x) ∞/1–q

0

eυ,q(–[n]qt)[n]qk+2υθktk+2υθk

[k+ 2υθk]q!

×fqk+2υθk_td

qt, (1.7)

where

Qυ_n,q(x) =([n]qx)

k

γυ,q(k)

q

(k+2υθk)(k+2υθk+1)

2 _.

For the proof of a basic estimate, we use the generalizedq-gamma function.

Definition 1.1 The generalizedq-gamma function is defined by

Γq(t) =

1/1–q

0

γ_qA(t) =

∞/A(1–q) 0

xt–1eq(–x) dqx, t> 0, (1.9)

whereΓq(t) =K(A;t)γqA(t) andK(A;t) = 1+1AA t_{(1 +} 1

A) t

q(1 +A)tq–1. Moreover, for any

pos-itive integer n, we haveK(A;n) =qn(n2–1) _{andΓq(n) =q}

n(n–1) 2 _γA

q(n), which also satisfy the

following equation:

Γq(t+ 1) =

⎧ ⎨ ⎩

[t]qΓq(t) fort> 0,

1 fort= 0. (1.10)

For more details, see [8].

2 Estimation of moments

Lemma 2.1 LetP_n∗_,q(·;·)be the operators defined by(1.7).Then,we have

(1) P_n∗_,q(1;x) = 1, (2) P_n∗_,q(t;x) =x+ 1

q[n]q

,

(3) P_n∗_,qt2;x≤(1 +q) q3_[n]2

q

+ 1

q2_[n]

q

1 + 2q+q2[1 + 2υ]q

x+x2,

P∗

n,q

t2;x≥(1 +q) q3_[n]2

q

+ 1

q2_[n]

q

1 + 2q+q2(1+υ)[1 – 2υ]q

eυ,q(q[n]qx)

eυ,q([n]qx)

x+x2,

(4) P_n∗_,qt3;x≤(1 +q)(1 +q+q

2₎

q6_[n]3

q

+ 1

q5_[n]2

q

1 + 3q+ 4q2+ 3q3+q21 + 2q+ 3q2[1 + 2υ]q

+q5[1 + 2υ]2_qx

+ 1

q4_[n]

q

q1 + 2q+ 3q2+ 3q4[1 + 2υ]q

x2+x3,

(5) P_n∗_,qt4;x≤(1 +q)(1 + 2q+ 3q

2_{+ 3q}3_{+ 2q}4_+q5₎

q10_[n]4

q

+ 1

q9_[n]3

q

1 + 4q+ 8q2+ 12q3+ 12q4+ 9q5+ 4q6

+q21 + 3q+ 7q2+ 9q3+ 9q4+ 6q5[1 + 2υ]q

+q51 + 2q+ 3q2+ 4q3[1 + 2υ]2_q+q9[1 + 2υ]3_qx

+ 1

q8_[n]2

q

q1 + 3q+ 7q2+ 9q3+ 9q4+ 6q5

+q41 + 2q+ 3q2+ 4q3[1 + 2υ]q+ 7q8[1 + 2υ]2q

x2

+ 1

q7_[n]

q

q31 + 2q+ 3q2+ 4q3+ 6q7[1 + 2υ]q

Proof We prove this lemma by using the definition of generalizedq-gamma function de-fined by Definition1.1. More precisely,

= 1 q3_[n]2

qeυ,q([n]qx)

×

∞

k=0

([n]qx)k

γυ,q(k)

(1 +q) +q(1 + 2q)[k+ 2υθk]q+q3[k+ 2υθk]2q

=(1 +q) q3_[n]2

q

+(1 + 2q) q2_[n]

q

x+ 1

[n]2

qeυ,q([n]qx)

∞

k=0

([n]qx)k

γυ,q(k)

[k+ 2υθk]2q.

From [11] and by (1.6), we obtain

[n]2_qx2+q2υ[1 – 2υ]q

eυ,q(q[n]qx)

eυ,q([n]qx)

[n]qx≤

1 [n]2

qeυ,q([n]qx)

∞

k=0

([n]qx)k

γυ,q(k)

≤[n]2_qx2+ [1 + 2υ]q[n]qx.

Foru= 3,f(t) =t3and foru= 4,f(t) =t4, we get

P∗

n,q

t3;x= 1 q4_[n]3

qeυ,q([n]qx)

∞

k=0

([n]qx)k

γυ,q(k)

[k+ 2υθk+ 3]q[k+ 2υθk+ 2]q[k+ 2υθk+ 1]q

and

P∗

n,q

t4;x= 1 q10_[n]4

qeυ,q([n]qx)

∞

k=0

([n]qx)k

γυ,q(k)

×[k+ 2υθk+ 4]q[k+ 2υθk+ 3]q[k+ 2υθk+ 2]q[k+ 2υθk+ 1]q.

A simple calculation leads to

[k+ 2υθk+ 3]q[k+ 2υθk+ 2]q[k+ 2υθk+ 1]q

= (1 +q)1 +q+q2+q(1 + 2q)1 +q+q2+q3(1 +q)[k+ 2υθk]q

+q31 +q+q2+q4(1 + 2q)[k+ 2υθk]2q+q6[k+ 2υθk]3q,

[k+ 2υθk+ 4]q[k+ 2υθk+ 3]q[k+ 2υθk+ 2]q[k+ 2υθk+ 1]q

= (1 +q)1 + 2q+ 3q2+ 3q3+ 2q4+q5+q(1 + 2q)1 + 2q+ 3q2+ 3q3+ 2q4+q5

+q3(1 +q)1 + 2q+ 2q2+ 2q3[k+ 2υθk]q

+q31 + 2q+ 3q2+ 3q3+ 2q4+q5

+q4(1 + 2q)1 + 2q+ 2q2+ 2q3+q7(1 +q)[k+ 2υθk]2q

+q61 + 2q+ 2q2+ 2q3+q8(1 + 2q)[k+ 2υθk]3q+q10[k+ 2υθk]4q.

Hence by using the result forDn,q(f;x) defined by (1.6) withf(t) =t3andf(t) =t4(see [11]),

we get the required result.

Lemma 2.2 LetP_n∗_,q(·;·)be the operators defined by(1.7).Then,we have

1◦ P_n∗_,q(t–x);x= 1 q[n]q

2◦ P_n∗_,q(t–x)2;x≤(1 +q) q3_[n]2

q

+ 1

q2_[n]

q

1 +q2[1 + 2υ]q

x,

P∗

n,q

(t–x)2;x≥(1 +q) q3_[n]2

q

+ 1

q2_[n]

q

1 +q2(1+υ)[1 – 2υ]q

eυ,q(q[n]qx)

eυ,q([n]qx)

x.

3 Korovkin and weighted Korovkin type approximation

Korovkin’s approximation theory [4] has many applications in classical approximation the-ory, as well as in other branches of mathematics. In this section we obtained some approx-imation results via well known Korovkin’s type theorem and weighted Korovkin’s type theorem for the operators defined by (1.7).

LetCB(R+) be the set of all bounded and continuous functions onR+= [0,∞), which is

a linear normed space with

fCB=sup

x≥0

f(x).

Let

E:=

f :x∈[0,∞), f(x)

1 +x2 is convergent asx→ ∞

.

In order to obtain the convergence results for the operatorsP_n∗_,q(·;·) defined by (1.7), we takeq=qn(0 <qn< 1) such that

lim

n→∞qn= 1 and nlim→∞q n

n=α, (3.1)

for some constantα(0α< 1).

Theorem 3.1 Let q=qn,with0 <qn< 1, satisfy(3.1).Then,for any function f ∈C[0,

∞)∩E,

lim

n→∞P ∗

n,qn(f;x) =f(x).

Proof The proof is based on the well-known Korovkin’s theorem regarding the conver-gence of a sequence of linear and positive operators, so it is enough to prove the conditions

lim

n→∞P ∗

n,qn

tj;x=xj, j= 0, 1, 2,

uniformly on [0, 1]. Clearly, _[n1_]

q →0, (n→ ∞) we have

lim

n→∞P

∗

n,qn(t;x) =x, _nlim_→∞P

∗

n,qn

t2;x=x2.

This completes the proof.

We recall the weighted spaces of functions onR+_{, which are defined as follows:}

Pσ

R+_=f:f(x)≤M

fσ(x)

Qσ

R+_=f:f∈P

σ

R+_∩C[0,∞),

Qkσ

R+₌

f:f∈Qσ

R+_{and lim}

x→∞

f(x)

σ(x)=k(kis a constant)

,

whereσ(x) = 1 +x2_{is a weight function andM}

f is a constant depending only onf. Note

thatQσ(R+) is a normed space with the normfσ=supx≥0| f(x)|

σ(x).

Theorem 3.2 Let q=qn,with0 <qn< 1,satisfy(3.1).Then,for any function f ∈Qkσ(R+),

we have

lim

n→∞P ∗

n,qn(f;·) –fσ= 0.

Proof Takef(t) =tτ_{. Then sincef(t)∈C}k

σ(R+), by Korovkin’s theorem, it satisfiesPn∗,qn(t

τ_;

x)→xτ _{uniformly, whenevern→ ∞. Therefore, by applying Lemma2.1, sinceP}∗

n,qn(1; x) = 1, we have

lim

n→∞P ∗

n,qn(1;·) – 1σ = 0 (3.2)

and

_P∗

n,qn(t;x) –·σ = sup

x∈[0,∞)

|P∗

n,qn(t;x) –x| 1 +x2

= 1

qn[n]qn sup

x∈[0,∞)

1 1 +x2.

Then, clearly,_[n1_]

qn →0 asn→ ∞, which implies that

lim

n→∞P

∗

n,qn(t;·) –xσ = 0. (3.3)

In similar way,

_P∗

n,qn

t2;·–x2_σ = sup

x∈[0,∞)

|P∗

n,qn(t

2_{;x) –x}2_|

1 +x2

= 1

q2

n[n]qn

1 + 2qn+q2n[1 + 2υ]qn

sup

x∈[0,∞)

x 1 +x2

+(1 +qn) q3

n[n]2qn sup

x∈[0,∞)

1 1 +x2.

Thus we have

lim

n→∞P ∗

n,qn

t2;·–x2_σ = 0. (3.4)

This completes the proof.

4 Order of approximation

by

continuity defined by(4.1).

Proof We prove it by using (4.1)–(4.2) and Cauchy–Schwarz inequality. Indeed, _P∗

Corollary 4.2 Forδn=Pn∗,qn((q

k+2υθk

n t–x)2;x),we have

_P∗

n,qn(f;x) –f(x)≤2ω(f;δn).

5 Rate of convergence

Now we give the rate of convergence of the operatorsP_n∗_,q(f;x) in terms of the elements of

Proof We prove it by using (5.1) and Hölder’s inequality. Indeed, _P∗

LetCB[0,∞) denote the space of all bounded and continuous functions defined onR+=

[0,∞) and

C_B2R+=ψ∈CB

R+_:ψ,ψ∈C

B

R+_{, (5.2)}

with the norm

ψ_C2

B(R+)=ψCB(R+)+ψ

CB(R+)+ψ

CB(R+), (5.3)

also set

ψCB(R+)=sup

x∈R+

ψ(x). (5.4)

Theorem 5.2 LetP_n∗_,q(·;·)be the operators defined by(1.7).Then,for q=qn such that

qn∈(0, 1)and anyψ∈CB2(R+),

_P∗

n,qn(ψ;x) –ψ(x)≤

n,qn+Φn,qn(x)

ψ_C2

B(R+), wheren,qn=

1

qn[n]qn +

1 2q2n[n]2qn(1 +

1

qn)andΦn,qn(x) =

1

2qn2[n]qn(1 +qn

2_{[1 + 2υ]}

qn)x. Proof Letψ∈C2

B(R+). Then, by using the generalized mean value theorem in the Taylor

series expansion, we have

ψ(t) =ψ(x) +ψ(x)(t–x) +ψ(ϕ)(t–x)

2

2 , ϕ∈(x,t).

By applying the linearity property ofP_n∗_,qn, we have

P∗

n,qn(ψ;x) –ψ(x) =ψ

_(x)P∗

n,qn

(t–x);x+ψ

_(ϕ)

2 P

∗

n,qn

(t–x)2_;x,

which implies that

_P∗

n,qn(ψ;x) –ψ(x) ≤

1 qn[n]qn

ψ_C

B(R+) +

(1 +qn)

q3

n[n]2qn

+ 1

q2

n[n]qn

1 +qn2[1 + 2υ]qn

x

ψCB(R+)

2 .

From (5.3) we haveψCB(R+)≤ ψC_B2(R+₎andψCB(R+)≤ ψC2_B(R+₎, as well as

_P∗

n,qn(ψ;x) –ψ(x) ≤

1 qn[n]qn

ψ_C2

B(R+) +

(1 +qn)

qn3[n]2qn

+ 1

qn2[n]qn

1 +qn2[1 + 2υ]qn

x _ψ

C_B2(R+₎

2 .

6 Direct theorem

In 1968, J. Peetre [22] introduced a functional known as Peetre’s K-functional, which is defined by

K2(f;δ) =inf

f –ψCB(R+)+δψC_B2(R+₎

:ψ∈C_B2R+. (6.1)

There exits a positive constantC> 0 such thatK2(f,δ)≤Cω2(f,δ

1

2_{),δ> 0, where the}

second-order modulus of continuity is given by

ω2(f;δ) = sup 0<h<δ

sup

x∈R+

f(x+ 2h) – 2f(x+h) +f(x). (6.2)

Theorem 6.1 For f ∈CB(R+),x∈[0,∞)and q=qnsatisfying(3.1),we have

_P∗

n,qn(f;x) –f(x) ≤2D

ω2

f;

n,qn+Φn,qn(x) 2

+min

1,n,qn+Φn,qn(x) 2

fCB(R+)

,

whereDis a positive constant.

Proof We prove this by using Theorem5.2. Letψ∈CB(R+), then

_P∗

n,qn(f;x) –f(x)≤P

∗

n,qn(f–ψ;x)+P

∗

n,qn(ψ;x) –ψ(x)+f(x) –ψ(x) ≤2f–ψCB(R+)+

n,qn+Φn,qn(x)

ψ_C2

B(R+) = 2

f–ψCB(R+)+

n,qn+Φn,qn(x)

2 ψCB2(R+)

.

By taking the infimum over allψ∈C2

B(R+) and using (6.1), we get

_P∗

n,qn(f;x) –f(x)≤2K2

f;n,qn+Φn,qn(x) 2

.

Now, for an absolute constantD> 0 provided in [7], we use the relation

K2(f;δ)≤D

ω2(f;√δ) +min(1,δ)f.

This completes the proof.

Atakut and Ispir [5] introduced the weighted modulus of continuity defined as

Ω(f;δ) = sup

x∈[0,∞),|h|≤δ

|f(x+h) –f(x)|

(1 +h2_{)(1 +x}2₎, (6.3)

for an arbitraryf ∈Qk

σ(R+). The two main properties of this modulus of continuity are

limδ→0Ω(f;δ) = 0 and

_{f(t) –f(x)≤21 +}|t–x|

δ

1 +δ21 +x21 + (t–x)2Ω(f;δ), (6.4)

Theorem 6.2 Let q=qnbe numbers such that qn∈(0, 1)as n→ ∞.Then,for every f ∈

Qk

σ(R+),

sup

x∈[0,χυ,qn(n))

|P∗

n,qn(f;x) –f(x)| 1 +x2 ≤C

1 +χυ,qn(n)

Ω(f;√χυ,qn),

where the positive constantC= 1 +C1+ 4C2and

χυ,qn(n) =max

(1 +qn)

qn3[n]2qn

, 1

qn2[n]qn

1 +qn2[1 + 2υ]qn

.

Proof We use (6.3)–(6.4) and the Cauchy–Schwarz inequality. Thus we have _P∗

n,qn(f;x) –f(x)

≤21 +δ21 +x2Ω(f;δ)

×

1 +P_n∗_,qn(t–x)2;x+P_n∗_,qn1 + (t–x)2|t–x|

δ ;x

(6.5)

and

P∗

n,qn

1 + (t–x)2|t–x|

δ ;x

≤2P_n∗_,qn1 + (t–x)4;x

1 2

P∗

n,qn

(t–x)2 δ2 ;x

1 2

. (6.6)

From Lemma2.2, we easily see that

P∗

n,qn

(t–x)2;x≤χυ,qn(n)(1 +x), (6.7)

where

χυ,qn(n) =max

(1 +qn)

qn3[n]2qn

, 1

qn2[n]qn

1 +qn2[1 + 2υ]qn

.

Now there exits a constantC1> 0 such that

P∗

n,qn

(t–x)2;x≤C1(1 +x). (6.8)

We easily conclude that

P∗

n,qn

(t–x)4;x≤ 24 q10

n[n]4qn

+ 1

q9

n[n]3qn

26 + 35[1 + 2υ]qn+ 10[1 + 2υ]

2

qn+ [1 + 2υ]

3

qn

x

+ 1

q8

n[n]2qn

3 – 14[1 + 2υ]qn+ 3[1 + 2υ]

2

qn

x2

+ 1

q5

n[n]qn

–10 – 6[1 + 2υ]qn

x3+ 8x4

≤ξυ,qn(n)

where

ξυ,qn(n) = max

24 q10

n [n]4qn , 1

q9

n[n]3qn

26 + 35[1 + 2υ]qn+ 10[1 + 2υ]

2

qn+ [1 + 2υ]

3

qn

,

1 q8

n[n]2qn

3 – 14[1 + 2υ]qn+ 3[1 + 2υ]2qn

, 1 q5

n[n]qn

–10 – 6[1 + 2υ]qn

, 8

.

Since,lim_n→∞ 1

[n]i_qn = 0 for alli= 1, 2, 3, 4 andlimn→∞qn= 1, for a constantC1> 0, we

have

P∗

n,qn

1 + (t–x)4;x

1 2 ≤C

2

2 +x+x2+x3+x4

1

2_{. (6.9)}

In the view of (6.7), we easily see that

P∗

n,qn

(t–x)2 δ2 ;x

1 2

≤1

δ

χυ,qn(n) 1

2_{(1 +x)}1_{2. (6.10)}

Finally, in the light of equation (6.5) by combining (6.6)–(6.10), if we choose δ =

χυ,qn(n) and take the supremum overx∈[0,χυ,qn(n)), we get the desired result.

Funding

The second author would like to thank Prince Sultan University for funding this work through research group “Nonlinear Analysis Methods in Applied Mathematics (NAMAM)” group number RG-DES-2017-01-17.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

The authors contributed equally and significantly in writing this paper. All authors read and approved the final manuscript.

Author details

1_{Department of Computer Science (SEST), Jamia Hamdard, New Delhi, India.}2_{Department of Mathematics and General}

Sciences, Prince Sultan University, Riyadh, Saudi Arabia.3_{Department of Mathematics, Aligarh Muslim University, Aligarh,}

India.

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Received: 17 December 2018 Accepted: 4 June 2019

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