Theory and Modern Applications

# Trigonometric approximation of functions $$f(x,y)$$ of generalized Lipschitz class by double Hausdorff matrix summability method

## Abstract

In this paper, we establish a new estimate for the degree of approximation of functions $$f(x,y)$$ belonging to the generalized Lipschitz class $$Lip ((\xi _{1}, \xi _{2} );r )$$, $$r \geq 1$$, by double Hausdorff matrix summability means of double Fourier series. We also deduce the degree of approximation of functions from $$Lip ((\alpha ,\beta );r )$$ and $$Lip(\alpha ,\beta )$$ in the form of corollary. We establish some auxiliary results on trigonometric approximation for almost Euler means and $$(C, \gamma , \delta )$$ means.

## 1 Introduction

The study of various summability means of double Fourier series have been done by several authors, for example, Chow [2], Sharma [11], Łenski [6], and Ustina [15]. Dealing with the first arithmetic means of double Fourier series, Hasegawa [4] obtained the following:

### Theorem A

If a continuous function $$f(x, y)$$ of period 2π with respect to both x and y belongs to $$Lip (\alpha , \beta )$$, where $$0<\alpha <l$$ and $$0<\beta <1$$, then

$$\bigl\vert \sigma _{m,n}(x,y) -f(x,y) \bigr\vert = O \bigl( m^{-\alpha }+n^{- \beta } \bigr)$$

uniformly in $$(x, y)$$ as m and n independently tend to infinity.

If $$\alpha =\beta =1$$, then

$$\bigl\vert \sigma _{m,n}(x,y) -f(x,y) \bigr\vert = O \bigl( m^{-1} \log m +n^{-1} \log n \bigr)$$

uniformly in $$(x, y)$$ as m and n independently tend to infinity.

Siddiqui and Mohammadzadeh [12] investigated the approximation by Cesàro and B means of double Fourier series. Stepanets [13, 14] has established estimates of approximation for certain classes of periodic functions and differentiable periodic functions of two variables by linear methods of summation of their Fourier sums. Móricz and Shi [8] proved the following result for the approximation to continuous functions by Cesàro means of double Fourier series.

### Theorem B

If $$f \in E(\alpha , \beta )$$, $$0 < \alpha$$, $$\beta \leq 1$$, $$\gamma , \delta \geq 0$$, then

\begin{aligned} \bigl\| \sigma _{mn}^{\gamma \delta } (f,x,y) - f(x,y\bigr\| =& O \biggl( \frac{1}{(m+1)^{\alpha }}+ \frac{1}{(n+1)^{\beta }} \biggr) \quad \textit{if } 0 < \alpha , \beta \leq 1, \\ =& O \biggl( \frac{1}{(m+1)^{\alpha }}+ \frac{\log (n+2)}{(n+1)} \biggr) \quad \textit{if } 0 < \alpha < \beta = 1, \\ =& O \biggl( \frac{\log (m+2)}{(m+1)}+ \frac{\log (n+2)}{(n+1)} \biggr) \quad \textit{if } \alpha = \beta = 1. \end{aligned}

The degree of approximation using Gauss–Weierstrass integrals was also investigated by Khan and Ram [5]. Recently, error and bounds of certain bivariate functions by almost Euler means of double Fourier series for the functions of Lipschitz and Zygmund classes was estimated by Rathor and Singh [9]. To find the approximation of functions of two-dimensional torus, in this paper, we obtain a new estimate for trigonometric approximation of functions $$f(x,y)$$ of generalized Lipschitz class by double Hausdorff matrix summability method of double Fourier series. For other summability methods of approximation, see [1] and [7].

## 2 Definitions and preliminaries

Let $$\sum_{m=0}^{\infty }\sum_{n=0}^{\infty } g_{m,n}$$ be double series with the sequence of $$(m,n)$$th partial sums

$$s_{m,n}=\sum_{j=0}^{m}\sum _{k=0}^{n} g_{j,k}.$$

A double Hausdorff matrix has the entries

$$h_{m,n}^{j,k}= \binom{m }{j} \binom{n }{k} \Delta ^{m-j}_{1} \Delta ^{n-k}_{2} \mu _{j,k},$$

where $$\{ \mu _{j,k} \}$$ is any real or complex sequence, and

$$\Delta ^{m-j}_{1} \Delta ^{n-k}_{2} \mu _{j,k} = \sum_{w=0}^{m-j} \sum _{z=0}^{n-k} (-1)^{j+k} \binom{m-j }{w} \binom{n-k }{z} \mu _{j+w,k+z} .$$

If $$t_{m,n}^{H} = \sum_{j=0}^{m}\sum_{k=0}^{n} h_{m,n}^{j,k} s_{j,k} \rightarrow g$$ as $$m \rightarrow \infty$$ and $$n \rightarrow \infty$$, then $$\sum_{m=0}^{\infty }\sum_{n=0}^{\infty } g_{m,n}$$ is said to be summable to the sum g by the double Hausdorff matrix summability method [15].

A necessary and sufficient condition for double Hausdorff matrix summability method to be regular is there exists a function $$\chi (s,t) \in BV[0,1]\times [0,1]$$ such that

$$\int _{0}^{1} \int _{0}^{1} \bigl\vert d \chi (s,t) \bigr\vert < \infty$$

and

$$\mu _{m,n} = \int _{0}^{1} \int _{0}^{1} s^{m} t^{n} \,d \chi (s,t),$$

where $$\chi (s,0)=\chi (s,0^{+})=\chi (0^{+},t)=\chi (0,t) = 0$$, $$0\leq s$$, $$t \leq 1$$, and $$\chi (1,1)-\chi (1,0)-\chi (0,1)+\chi (0,0) = 1$$ [10].

It is easy to see that the absolute value of the measure $$d \chi (s,t)$$ can me majorized by $$K_{1} K_{2} \,ds \,dt$$ for some constants $$K_{1}$$ and $$K_{2}$$ (see [16]).

The important particular cases of double Hausdorff matrix summability means are as follows:

1. 1

Almost Euler summability means ($$(E,q_{1},q_{2})$$ means) if $$\mu _{m,n} = \frac{1}{(1+q_{1})^{m}}\frac{1}{(1+q_{2})^{n}}$$.

2. 2

$$(E,1,1)$$ means if $$q_{1}=1$$ and $$q_{2}=1$$ in $$(E,q_{1},q_{2})$$ means.

3. 3

$$(C, \gamma , \delta )$$ means if $$\mu _{m,n} = \frac{1}{A^{\gamma }_{m}}\frac{1}{A^{\delta }_{n}}$$, where $$\gamma , \delta \geq -1$$ and $$A^{\gamma }_{m} = \binom{{\gamma +m} }{m }$$, $$A^{\delta }_{n} = \binom{{\delta +n} }{n }$$.

4. 4

$$(C,1,1)$$ means if $$\gamma =\delta =1$$ in $$(C, \gamma , \delta )$$ means.

Let $$f(x,y)$$ be a Lebesgue-integrable function of period 2π with respect to both variables x and y and summable in the fundamental square $$Q:(-\pi ,\pi ) \times (-\pi ,\pi )$$. The double Fourier series of $$f(x,y)$$ is given by

\begin{aligned} f(x,y)&=\sum_{m=0}^{\infty } \sum_{n=0}^{\infty } \lambda _{m,n} [ a_{m,n} \cos mx \cos ny +b_{m,n} \sin mx \cos ny \\ &\quad{} + c_{m,n} \cos mx \sin ny + d_{m,n} \sin mx \cos ny ] \end{aligned}
(1)

with $$(m,n)$$th partial sums $$s_{m,n}(f;(x,y))$$, where

\begin{aligned}& \lambda _{m,n}= \textstyle\begin{cases} 1/4 & \text{for } m=n=0, \\ 1/2 & \text{for } m>0, n=0 \mbox{ and } m=0, n>0, \\ 1 & \text{for } m>0, n>0 , \end{cases}\displaystyle \\& a_{m,n}=\pi ^{-2} \iint _{Q} f(x,y) \cos mx \cos ny \,dx \,dy, \end{aligned}

and similar expressions for $$b_{m,n}$$, $$c_{m,n}$$, and $$d_{m,n}$$ [3].

We define the $$L^{r}$$ norm by

$$\Vert f \Vert _{r}= \textstyle\begin{cases} \{ \frac{1}{4\pi } \int _{0}^{2\pi } \int _{0}^{2\pi } \vert f(x,y) \vert ^{r} \,dx \,dy \} ^{1/r}, & r\geq 1, \\ \operatorname*{ess\,sup}_{0\leq x,y \leq 2\pi } \vert f(x,y) \vert , & r=\infty . \end{cases}$$

The degree of approximation of a function $$f :\mathbb{R}^{2} \rightarrow \mathbb{R}$$ by a trigonometric polynomial [17]

\begin{aligned} t_{m,n}(x,y)&=\sum _{j=0}^{m}\sum_{k=0}^{n} \lambda _{m,n} [ a_{j,k} \cos mx \cos ny +b_{j,k} \sin mx \cos ny \\ &\quad {}+ c_{j,k} \cos mx \sin ny + d_{j,k} \sin mx \cos ny ] \end{aligned}

of order $$(m+n)$$ is defined by

$$E_{m,n}\bigl(f,L^{r}\bigr) =\min_{0\leq x,y \leq2\pi} \Vert t_{m,n}-f \Vert _{r} .$$

A function $$f :\mathbb{R}^{2} \rightarrow \mathbb{R}$$ of two variables x and y is said to belong to the class $$Lip(\alpha ,\beta )$$ [4] if

$$\bigl\vert f(x+u,y+v)-f(x,y) \bigr\vert =O\bigl( \vert u \vert ^{\alpha } + \vert v \vert ^{\beta }\bigr), \quad 0< \alpha \leq 1, 0< \beta \leq 1,$$

to the class $$Lip ((\alpha ,\beta );r )$$ if

$$\biggl\{ \frac{1}{4\pi } \int _{0}^{2\pi } \int _{0}^{2\pi } \bigl\vert f(x+u,y+v)-f(x,y) \bigr\vert ^{r} \,dx \,dy \biggr\} ^{1/r}= O \bigl( \vert u \vert ^{\alpha } + \vert v \vert ^{\beta } \bigr),\quad r\geq 1,$$

and to the class $$Lip ((\xi _{1},\xi _{2});r )$$ if

$$\biggl\{ \frac{1}{4\pi } \int _{0}^{2\pi } \int _{0}^{2\pi } \bigl\vert f(x+u,y+v)-f(x,y) \bigr\vert ^{r} \,dx \,dy \biggr\} ^{1/r}= O \bigl(\xi _{1}(u) + \xi _{2}(v) \bigr),\quad r\geq 1,$$

where $$\xi _{1}$$ and $$\xi _{2}$$ are moduli of continuity, that is, nonnegative nondecreasing continuous functions such that $$\xi _{1}(0) =\xi _{2}(0) = 0$$, $$\xi _{1}(u_{1} + u_{2}) \le \xi _{1}(u_{1}) + \xi _{1}(u_{2})$$, and $$\xi _{2}(v_{1} + v_{2}) \le \xi _{2}(v_{1}) + \xi _{2}(v_{2})$$.

If $$\xi _{1}(u)=u^{\alpha }$$ and $$\xi _{2}(v)=v^{\beta }$$, $$0<\alpha \leq 1$$, $$0 < \beta \leq 1$$, then the class $$Lip ((\xi _{1},\xi _{2});r )$$ coincides with $$Lip ((\alpha ,\beta );r )$$. As $$r \rightarrow \infty$$, $$Lip ((\alpha ,\beta );r )$$ reduces to $$Lip(\alpha ,\beta )$$. Clearly, $$Lip(\alpha ,\beta ) \subseteq Lip ((\alpha ,\beta );r ) \subseteq Lip ((\xi _{1},\xi _{2});r )$$.

We define the forward difference operator Δ as $$\Delta \mu _{k} = \mu _{k} - \mu _{k+1}$$; also, $$\Delta ^{n+1}\mu _{k}=\Delta (\Delta ^{n} \mu _{k} )$$, $$k\geq 0$$. We denote

\begin{aligned}& \begin{aligned} \phi (u,v)&=(1/4) \bigl[f(x+u,y+v)+f(x+u,y-v) +f(x-u,y+v)+ f(x-u,y-v) \\ &\quad{} -4f(x,y) \bigr], \end{aligned} \\& M_{m}^{H}(u)= \frac{K_{1}}{2\pi }\sum _{j=0}^{m} \int _{0}^{1} \binom{m }{j} s^{j} (1-s)^{m-j} \,ds \frac{\sin (j+\frac{1}{2} )u}{\sin \frac{u}{2}}, \\& K_{n}^{H}(v) = \frac{K_{2}}{2\pi }\sum _{k=0}^{n} \int _{0}^{1} \binom{N }{K} t^{k} (1-t)^{n-k} \,dt \frac{\sin (k+\frac{1}{2} )v}{\sin \frac{v}{2}}. \end{aligned}

## 3 Result

The object of this paper is obtaining the degree of approximation of functions $$f(x,y)$$ of generalized Lipschitz class by double Hausdorff matrix summability means of its double Fourier series:

### Theorem 1

If $$f(x,y)$$ is a 2π periodic function with respect to both variables x and y, Lebesgue integrable in $$(-\pi ,\pi )\times (-\pi ,\pi )$$ and belonging to the class $$Lip ((\xi _{1}, \xi _{2});r )$$ ($$r \geq 1$$), then the degree of approximation of $$f(x,y)$$ by double Hausdorff matrix summability means

$$t_{m,n}^{H}= \sum_{j=0}^{m} \sum_{k=0}^{n} \int _{0}^{1} \int _{0}^{1} \binom{m }{j} \binom{n }{k} s^{j}(1-s)^{m-j} t^{k}(1-t)^{n-k} \,d \chi (s,t) s_{j,k}$$

of double Fourier series (1) satisfies

$$\begin{gathered} \bigl\Vert t_{m,n}^{H} - f \bigr\Vert _{r} = O \biggl(\frac{1}{(m+1)} \int _{\frac{1}{m+1}}^{\pi } \frac{ \xi _{1}(u)}{u^{2}} \,du + \frac{1}{(n+1)} \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr) \\ \quad \textit{for } m,n=0,1,2,\dots . \end{gathered}$$
(2)

## 4 Lemmas

For the proof of our theorems, we need the following lemmas.

### Lemma 1

$$\vert M_{m}^{H}(u) \vert = O (m+1 )$$ for $$0< u \leq \frac{1}{m+1}$$, and $$\vert K_{n}^{H}(v) \vert = O (n+1 )$$ for $$0< v \leq \frac{1}{n+1}$$.

### Proof

Since $$\vert \sin mu \vert \leq mu$$ for $$0< u\leq \frac{1}{m+1}$$ and $$\sin (u/2)\geq (u/\pi )$$, we have

\begin{aligned} \bigl\vert M_{m}^{H}(u) \bigr\vert =& \Biggl\vert \frac{K_{1}}{2\pi }\sum_{j=0}^{m} \int _{0}^{1} \binom{m }{j} s^{j} (1-s)^{m-j} \,ds \frac{\sin (j+\frac{1}{2} )u}{\sin \frac{u}{2}} \Biggr\vert \\ =& \frac{K_{1}}{2\pi }\sum_{j=0}^{m} \int _{0}^{1} \binom{m }{j} s^{j} (1-s)^{m-j} \,ds \frac{ \vert \sin (j+\frac{1}{2} )u \vert }{ \vert \sin \frac{u}{2} \vert } \\ \leq & \frac{K_{1}}{2\pi }\sum_{j=0}^{m} \int _{0}^{1} \binom{m }{j} s^{j} (1-s)^{m-j} \,ds \frac{ (j+ \frac{1}{2} )u }{ \vert \frac{u}{\pi } \vert } \\ =& K_{1} \pi \biggl(m+ \frac{1}{2} \biggr) \int _{0}^{1} \sum_{j=0}^{m} \binom{m }{j} s^{j} (1-s)^{m-j} \,ds \\ =& K_{1} \pi \biggl(m+ \frac{1}{2} \biggr) \int _{0}^{1} ( s+1-s)^{m} \,ds \\ =& O ( m+1 ). \end{aligned}

Similarly, for $$0< v \leq \frac{1}{n+1}$$,

$$\big\vert K_{n}^{H}(v) \big\vert = O ( n+1 ).$$

□

### Lemma 2

$$\vert M_{m}^{H}(u) \vert = O (\frac{1}{(j+1)u^{2}} )$$ for $$\frac{1}{m+1} < u \leq \pi$$, and $$\vert K_{n}^{H}(v) \vert = O (\frac{1}{(k+1)v^{2}} )$$ for $$\frac{1}{n+1} < v \leq \pi$$.

### Proof

Since $$\sin (m+1) u \leq 1$$ for $$\frac{1}{m+1} < u \leq \pi$$ and $$\sin (u/2)\geq (u/\pi )$$, we get

\begin{aligned} \Biggl\vert \sum_{j=0}^{m} \int _{0}^{1} \binom{m }{j} s^{j} (1-s)^{m-j} e^{i (j+\frac{1}{2} )u} \,ds \Biggr\vert =& \int _{0}^{1} e^{iu/2} \sum _{j=0}^{m} \binom{m }{j} s^{j} (1-s)^{m-j} e^{iju} \,ds \\ =& \int _{0}^{1} e^{iu/2} \bigl(1-s+s e^{iu} \bigr)^{m} \,ds \\ =& O \biggl(\frac{ 1}{(m+1)} \biggr) \biggl( \frac{e^{iu/2} (e^{i(m+1)u}-1 )}{e^{iu}-1} \biggr). \end{aligned}

Equating the imaginary parts of both sides, we get

$$\Biggl\vert \sum_{j=0}^{m} \int _{0}^{1} \binom{m }{j} s^{k} (1-s)^{m-j} \sin \biggl(k+\frac{1}{2} \biggr) \,ds \Biggr\vert = O \biggl( \frac{1}{(m+1)u} \biggr).$$

Therefore

\begin{aligned} \bigl\vert M_{m}^{H}(u) \bigr\vert =& \Biggl\vert \frac{K_{1}}{2\pi } \sum_{j=0}^{m} \int _{0}^{1} \binom{ m }{j } s^{j} (1-s)^{m-j} \frac{\sin (j+\frac{1}{2} )u}{\sin \frac{u}{2}} \,ds \Biggr\vert \\ \leq & \frac{K_{1}}{2 u} \Biggl\vert \sum_{j=0}^{m} \int _{0}^{1} \binom{ m }{j } s^{j} (1-s)^{m-j} \sin \biggl(j+\frac{1}{2} \biggr)u \,ds \Biggr\vert \\ =& O \biggl(\frac{1}{(m+1) u^{2}} \biggr). \end{aligned}

Similarly, for $$\frac{1}{n+1} < v \leq \pi$$,

$$\big\vert K_{n}^{H}(v) \big\vert = O \biggl(\frac{1}{(n+1)v^{2}} \biggr).$$

□

### Lemma 3

If $$f(x,y)\in Lip ((\xi _{1},\xi _{2});r )$$ ($$r\geq 1$$), then $$\Vert \phi (u,v)) \Vert _{r} = O ( \xi _{1}(u) + \xi _{2}(v) )$$.

### Proof

Clearly,

\begin{aligned}& \begin{aligned} \bigl\vert \phi (u,v) \bigr\vert &= \frac{1}{4} \bigl\vert f(x+u,y+v)+ f(x+u,y-v) +f(x-u,y+v) +f(x-u,y-v)-4f(x,y) \bigr\vert \\ &\leq \frac{1}{4} \bigl[ \bigl\vert f(x+u,y+v)-f(x,y) \bigr\vert + \bigl\vert f(x+u,y-v)-f(x,y) \bigr\vert \\ &\quad {} + \bigl\vert f(x-u,y+v)-f(x,y) \bigr\vert + \bigl\vert f(x-u,y-v)-f(x,y) \bigr\vert \bigr], \end{aligned} \\& \begin{aligned} \bigl\Vert \phi (u,v) \bigr\Vert _{r} &\leq \frac{1}{4} \bigl[ \bigl\Vert f(x+u,y+v)-f(x,y) \bigr\Vert _{r} + \bigl\Vert f(x+u,y-v)-f(x,y) \bigr\Vert _{r} \\ &\quad {} + \bigl\Vert f(x-u,y+v)-f(x,y) \bigr\Vert _{r} + \bigl\Vert f(x-u,y-v)-f(x,y) \bigr\Vert _{r} \bigr] \\ &= O \bigl( \xi _{1}(u)+\xi _{2}(v) \bigr). \end{aligned} \end{aligned}

□

## 5 Proof of Theorem 1

The $$(m,n)$$th partial sum of the double Fourier series (1) is given by

$$s_{m,n}\bigl(f;(x,y)\bigr)-f(x,y)=\frac{1}{4\pi ^{2}} \int _{0}^{\pi } \int _{0}^{\pi } \phi (u,v) \frac{\sin (m+\frac{1}{2})u \sin (n+\frac{1}{2})v }{\sin \frac{u}{2} \sin \frac{v}{2}} \,du \,dv.$$

Denoting the double Hausdorff matrix sums of $$s_{m,n}$$ by $$t_{m,n}^{H}$$, we have

\begin{aligned}& \begin{aligned}[b] t_{m,n}^{H} (x,y) -f(x,y) &= \sum _{j=0}^{m} \sum_{k=0}^{n} h_{m,n}^{j,k} \bigl\{ s_{j,k}\bigl(f;(x,y) \bigr)-f(x,y) \bigr\} \\ &= \int _{0}^{\pi } \int _{0}^{\pi } \phi (u,v) \sum _{j=0}^{m} \sum_{k=0}^{n} h_{m,n}^{j,k} \frac{\sin (j+\frac{1}{2})u \sin (k+\frac{1}{2})v }{\sin \frac{u}{2} \sin \frac{v}{2}} \,du \,dv \\ &= \int _{0}^{\pi } \int _{0}^{\pi } \phi (u,v) M_{m}^{H}(u) K_{n}^{H}(v) \,du \,dv, \end{aligned} \end{aligned}
(3)
\begin{aligned}& \bigl\Vert t_{m,n}^{H} - f \bigr\Vert _{r} = \int _{0}^{\pi } \int _{0}^{\pi } \bigl\Vert \phi (u,v) \bigr\Vert _{r} M_{m}^{H}(u) K_{n}^{H}(v) \,du \,dv \\& \hphantom{\bigl\Vert t_{m,n}^{H} - f \bigr\Vert _{r}}= \biggl( \int _{0}^{\frac{1}{m+1}} \int _{0}^{ \frac{1}{n+1}} + \int _{0}^{\frac{1}{m+1}} \int ^{\pi }_{ \frac{1}{n+1}}+ \int ^{\pi }_{\frac{1}{m+1}} \int _{0}^{ \frac{1}{n+1}} + \int ^{\pi }_{\frac{1}{m+1}} \int ^{ \pi }_{\frac{1}{n+1}} \biggr) \\ \end{aligned}
(4)
\begin{aligned}& \hphantom{\bigl\Vert t_{m,n}^{H} - f \bigr\Vert _{r}} \quad \bigl\Vert \phi (u,v) \bigr\Vert _{r} M_{m}^{H}(u) K_{n}^{H}(v) \,du \,dv \\& \hphantom{\bigl\Vert t_{m,n}^{H} - f \bigr\Vert _{r}}= I_{1}+I_{2}+I_{3}+I_{4}, \quad \text{say}. \end{aligned}
(5)

Using Lemmas 1 and 3, we obtain

\begin{aligned} \vert I_{1} \vert =& \int _{0}^{\frac{1}{m+1}} \int _{0}^{ \frac{1}{n+1}} \bigl\Vert \phi (u,v) \bigr\Vert _{r} M_{m}^{H}(u) K_{n}^{H}(v) \,du \,dv \\ =& O \biggl( \int _{0}^{\frac{1}{m+1}} \int _{0}^{ \frac{1}{n+1}} \bigl(\xi _{1}(u)+\xi _{2}(v)\bigr) (m+1) (n+1) \,du \,dv \biggr) \\ =& O \biggl( (m+1) (n+1) \int _{0}^{\frac{1}{m+1}} \int _{0}^{\frac{1}{n+1}} \bigl(\xi _{1}(u)+\xi _{2}(v)\bigr) \,du \,dv \biggr) \\ =&O \biggl[(m+1) (n+1) \biggl( \int _{0}^{\frac{1}{m+1}} \int _{0}^{\frac{1}{n+1}} \xi _{1}(u)\,du \,dv + \int _{0}^{ \frac{1}{m+1}} \int _{0}^{\frac{1}{n+1}} \xi _{2}(v)\,du \,dv \biggr) \biggr] \\ =&O \biggl[(m+1) (n+1) \biggl( \int _{0}^{\frac{1}{m+1}} \frac{\xi _{1}(u)}{n+1} \,du + \int _{0}^{\frac{1}{m+1}} \frac{\xi _{2} (\frac{1}{(n+1)} )}{n+1} \,dv \biggr) \biggr] \\ =& O \biggl[(m+1) (n+1) \biggl( \frac{\xi _{1} (\frac{1}{(m+1)} )}{(m+1)(n+1)} + \frac{\xi _{2} (\frac{1}{(n+1)} )}{(m+1)(n+1)} \biggr) \biggr] \\ =& O \biggl( \xi _{1} \biggl(\frac{1}{m+1} \biggr) +\xi _{2} \biggl( \frac{1}{n+1} \biggr) \biggr). \end{aligned}

Again by Lemmas 13, we have

\begin{aligned} \vert I_{2} \vert =&O \biggl[ \int _{0}^{\frac{1}{m+1}} \int ^{ \pi }_{\frac{1}{n+1}} \bigl(\xi _{1}(u)+\xi _{2}(v)\bigr) \frac{(m+1)}{(n+1)v^{2}} \,du \,dv \biggr] \\ =& O \biggl[ \frac{(m+1)}{(n+1)} \biggl( \int _{0}^{ \frac{1}{m+1}} \xi _{1}(u) \,du \int ^{\pi }_{\frac{1}{n+1}} \frac{dv}{v^{2}} + \int _{0}^{\frac{1}{m+1}} \,du \int ^{ \pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr) \biggr] \\ =& O \biggl[ \frac{(m+1)}{(n+1)} \biggl(\xi _{1} \biggl( \frac{1}{m+1} \biggr)\frac{1}{(m+1)} \biggl((n+1)-\frac{1}{\pi } \biggr) + \frac{1}{(m+1)} \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr) \biggr] \\ =& O \biggl( \xi _{1} \biggl(\frac{1}{m+1} \biggr) + \frac{1}{(n+1)} \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr). \end{aligned}
(6)

Similarly,

\begin{aligned} \vert I_{3} \vert =&O \biggl[ \int _{\frac{1}{m+1}}^{\pi } \int ^{ \frac{1}{n+1}}_{0} \bigl(\xi _{1}(u)+\xi _{2}(v)\bigr) \frac{(n+1)}{(m+1)u^{2}} \,du \,dv \biggr] \\ =& O \biggl[ \frac{(n+1)}{(m+1)} \biggl( \int _{\frac{1}{m+1}}^{ \pi } \frac{ \xi _{1}(u)}{u^{2}} \,du \int ^{\frac{1}{n+1}}_{0} \,dv + \int _{\frac{1}{m+1}}^{\pi } \frac{du}{u^{2}} \int ^{ \frac{1}{n+1}}_{0} \xi _{2}(v) \,dv \biggr) \biggr] \\ =& O \biggl(\frac{1}{(m+1)} \int _{\frac{1}{m+1}}^{\pi } \frac{ \xi _{1}(u)}{u^{2}} \,du + \xi _{2} \biggl(\frac{1}{n+1} \biggr) \biggr). \end{aligned}
(7)

Also, using Lemmas 2 and 3, we get

\begin{aligned} \vert I_{4} \vert =& O \biggl[ \int _{\frac{1}{m+1}}^{\pi } \int ^{ \pi }_{\frac{1}{n+1}} \bigl(\xi _{1}(u)+\xi _{2}(v)\bigr) \frac{1}{(m+1)u^{2}} \frac{1}{(n+1)v^{2}}\,du \,dv \biggr] \\ =& O \biggl[ \frac{1}{(m+1)(n+1)} \biggl( \int ^{\pi }_{ \frac{1}{m+1}} \frac{\xi _{1}}{u^{2}} \,du \int _{\frac{1}{n+1}}^{ \pi } \frac{1}{v^{2}} \,dv+ \int ^{\pi }_{\frac{1}{m+1}} \frac{1}{u^{2}} \,du \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}}{v^{2}} \,dv \biggr) \biggr] \\ =& O \biggl(\frac{1}{(m+1)} \int _{\frac{1}{m+1}}^{\pi } \frac{ \xi _{1}(u)}{u^{2}} \,du + \frac{1}{(n+1)} \int ^{\pi }_{ \frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr). \end{aligned}
(8)

Next,

\begin{aligned}& \begin{aligned} \frac{1}{(m+1)} \int ^{\pi }_{\frac{1}{m+1}} \frac{\xi _{1}(u)}{u^{2}} \,du &\geq \frac{1}{(m+1)} \xi _{1} \biggl(\frac{1}{m+1} \biggr) \int ^{ \pi }_{\frac{1}{m+1}} \frac{1}{u^{2}} \,dt \\ &=\frac{1}{(m+1)} \xi _{1} \biggl(\frac{1}{m+1} \biggr) \biggl\{ - \frac{1}{u} \biggr\} ^{\pi }_{\frac{1}{m+1}} \\ &=\xi _{1} \biggl(\frac{1}{m+1} \biggr) \biggl\{ 1- \frac{1}{(m+1)\pi } \biggr\} \\ &\geq \frac{1}{2} \xi _{1} \biggl(\frac{1}{m+1} \biggr), \end{aligned} \\& \text{or}\quad \xi _{1} \biggl(\frac{1}{m+1} \biggr) = O \biggl( \frac{1}{(m+1)} \int ^{\pi }_{\frac{1}{m+1}} \frac{\xi _{1}(u)}{u^{2}} \,dt \biggr) . \end{aligned}
(9)

Similarly,

$$\xi _{2} \biggl(\frac{1}{(n+1)} \biggr) = O \biggl( \frac{1}{(n+1)} \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dt \biggr).$$
(10)

Combining equations (5)–(10), we have

$$\bigl\Vert t_{m,n}^{H} - f \bigr\Vert _{r} = O \biggl(\frac{1}{(m+1)} \int _{\frac{1}{m+1}}^{\pi } \frac{ \xi _{1}(u)}{u^{2}} \,du + \frac{1}{(n+1)} \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr) .$$

This completes the proof of Theorem 1.

## 6 Corollaries

From the main theorem we derive the following corollaries.

### Corollary 1

If $$f(x,y)$$ is a 2π periodic function with respect to both variables x and y, Lebesgue integrable in $$(-\pi ,\pi )\times (-\pi ,\pi )$$ and belonging to the class $$Lip ((\alpha , \beta );r )$$ ($$r \geq 1$$), then the degree of approximation of $$f(x,y)$$ by means $$t_{m,n}^{H}$$ of double Fourier series (1) satisfies

\begin{aligned}& \bigl\Vert t_{m,n}^{H}-f \bigr\Vert _{r}= \textstyle\begin{cases} O ( (m+1)^{-\alpha }+(n+1)^{-\beta } ), & 0< \alpha < 1, 0< \beta < 1, \\ O ( (m+1)^{-\alpha }+ \frac{\log (n+1)\pi }{(n+1)} ), & 0< \alpha < 1, \beta =1, \\ O ( \frac{\log (m+1)\pi }{(m+1)} +(n+1)^{-\beta } ), & \alpha =1, 0< \beta < 1, \\ O ( \frac{\log (m+1)\pi }{(m+1)} + \frac{\log (n+1)\pi }{(n+1)} ), & \alpha =\beta =1, \end{cases}\displaystyle \end{aligned}

for $$m,n=0,1,2,\dots$$.

### Corollary 2

If $$f(x,y)$$ is a 2π periodic function with respect to both variables x and y, Lebesgue integrable in $$(-\pi ,\pi )\times (-\pi ,\pi )$$ and belonging to the class $$Lip(\alpha ,\beta )$$, then the degree of approximation of $$f(x,y)$$ by double Hausdorff matrix summability means $$t_{m,n}^{H}$$ of double Fourier series (1) satisfies

\begin{aligned}& \bigl\Vert t_{m,n}^{H}-f \bigr\Vert _{\infty }= \textstyle\begin{cases} O ( (m+1)^{-\alpha }+(n+1)^{-\beta } ), & 0< \alpha < 1, 0< \beta < 1, \\ O ( (m+1)^{-\alpha }+ \frac{\log (n+1)\pi }{(n+1)} ), & 0< \alpha < 1, \beta =1, \\ O ( \frac{\log (m+1)\pi }{(m+1)} +(n+1)^{-\beta } ), & \alpha =1, 0< \beta < 1, \\ O ( \frac{\log (m+1)\pi }{(m+1)} + \frac{\log (n+1)\pi }{(n+1)} ), & \alpha =\beta =1, \end{cases}\displaystyle \end{aligned}

for $$m,n=0,1,2,\dots$$.

### Corollary 3

If $$f(x,y)$$ is a 2π periodic function with respect to both variables x and y, Lebesgue integrable in $$(-\pi ,\pi )\times (-\pi ,\pi )$$ and belonging to the class $$Lip ((\xi _{1}, \xi _{2});r )$$, then the degree of approximation of $$f(x,y)$$ by almost Euler summability means

$$t_{m,n}^{E}= \frac{1}{(1+q_{1})^{m}} \frac{1}{(1+q_{2})^{n}}\sum _{j=0}^{m}\sum_{k=0}^{n} \binom{m }{j} \binom{n }{k} q_{1}^{m-j} q_{2}^{n-k} s_{j,k}$$

of double Fourier series (1) satisfies

$$\bigl\Vert t_{m,n}^{E} - f \bigr\Vert _{r} = O \biggl(\frac{1}{(m+1)} \int _{\frac{1}{m+1}}^{\pi } \frac{ \xi _{1}(u)}{u^{2}} \,du + \frac{1}{(n+1)} \int ^{\pi }_{\frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr)$$

for $$m,n=0,1,2,\dots$$.

### Corollary 4

For $$\gamma , \delta \geq -1$$, the Cesàro means $$\sigma _{m,n}^{\gamma , \delta }$$ of order γ and δ, that is, $$(C, \gamma , \delta )$$ means of double Fourier series, are given by

$$\sigma _{m,n}^{\gamma ,\delta }= \frac{1}{A^{\gamma }_{m}}\frac{1}{A^{\delta }_{n}}\sum _{j=0}^{m}\sum_{k=0}^{n} A_{m-j}^{\gamma -1} A_{n-k}^{\delta -1} s_{j,k},$$

where $$A^{\gamma }_{m} = \binom{{\gamma +m} }{m }$$ and $$A^{\delta }_{n} = \binom{{\delta +n} }{n }$$.

If $$f(x,y)$$ is a 2π periodic function with respect to both variables x and y, Lebesgue integrable in $$(-\pi ,\pi )\times (-\pi ,\pi )$$ and belonging to the class $$Lip ((\xi _{1}, \xi _{2});r )$$, then the degree of approximation of $$f(x,y)$$ by $$(C, \gamma , \delta )$$ means of double Fourier series (1), satisfies

$$\bigl\Vert \sigma _{m,n}^{\gamma ,\delta } - f \bigr\Vert _{r} = O \biggl( \frac{1}{(m+1)} \int _{\frac{1}{m+1}}^{\pi } \frac{ \xi _{1}(u)}{u^{2}} \,du + \frac{1}{(n+1)} \int ^{\pi }_{ \frac{1}{n+1}} \frac{\xi _{2}(v)}{v^{2}} \,dv \biggr)$$

for $$m,n=0,1,2,\dots$$.

## 7 Conclusion

We established the degree of approximation of a function $$f(x,y)$$ belonging to the generalized Lipschitz class by double Hausdorff matrix summability means of its double Fourier series in the form of equation (2). If $$\xi _{1}=u^{\alpha }$$ and $$\xi _{2}=v^{\beta }$$, then Theorem 1 reduces to Corollary 1, and as $$r \rightarrow \infty$$, Corollary 1 reduces to Corollary 2. Independent proofs of Corollaries 14 can be developed along the same lines as that of Theorem 1. Results similar to Corollaries 3 and 4 can be derived for $$(E,1,1)$$ means and $$(C,1,1)$$ means of its double Fourier series. In this way, we can obtain some more different results by changing $$\xi _{1}$$, $$\xi _{2}$$, and $$\mu _{m,n}$$ under given conditions. For functions $$f(x,y)$$ belonging to the Zygmund classes $$Zyg(\alpha ,\beta )$$ and $$Zyg(\alpha ,\beta ;p)$$ discussed in [9], the degree of approximation using double Hausdorff matrix summability means and hence almost Euler means of its double Fourier series can be obtained similarly to Theorem 1.

Not applicable.

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Not applicable.

Not applicable.

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Mishra, A., Mishra, V.N. & Mursaleen, M. Trigonometric approximation of functions $$f(x,y)$$ of generalized Lipschitz class by double Hausdorff matrix summability method. Adv Differ Equ 2020, 681 (2020). https://doi.org/10.1186/s13662-020-03124-8