Abstract
In this paper we consider trigonometric series with p-bounded variation coefficients. We presented a sufficient condition for uniform convergance of such series in case \(p>1\). This condition is significantly weaker than these obtained in the results on this subject known in the literature.
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1 Introduction
It is well known that there is a great number of interesting results in Fourier analysis established by assuming monotonicity of Fourier coefficients. The following classical convergence result can be found in many monographs (see for example [3, 18] or [1]).
Theorem 1
Suppose that \(b_{n}\ge b_{n+1}\) and \( b_{n}\rightarrow 0\) as \(n \rightarrow \infty \). Then a necessary and sufficient condition for the uniform convergence of the series
is \(nb_{n}\rightarrow 0\) as \(n \rightarrow \infty \).
This result has been generalized by weakening the monotonicity conditions of the coefficient (see for example [2, 14]). We present below a historical outline of the generalizations of this theorem.
In 2001 Leindler defined (see [8] and [10]) a new class of sequences named as sequences of Rest Bounded Variation, briefly denoted by RBVS, i.e.,
where here and throughout the paper \(C=C\left( a\right) \) always indicates a constant only depending on a and \(\Delta _ra_n = a_n-a_{n+r}\) for \(r \in \mathbb {N}\).
Denote by MS the class of monotone decreasing sequences, then it is clear that
Further, Tikhonov introduced a class of General Monotone Sequences GMS defined as follows (see [16]):
It is clear that
The class of GMS was generalized by Tikhonov (see [15]) and independently by Zhou, Zhou and Yu (see [17]) to the class of Mean Value Bounded Variation Sequences (MVBVS). We say that a sequence \( a:=\left( a_{n}\right) \) of complex numbers is said to be MVBVS if there exists \(\lambda \ge 2\) such that
holds for \(n \in \mathbb {N}\), where [x] is the integer part of x. They proved also in [17] that
Theorem 1 was generalized for the class RBVS in [8], for the class GMS in [16] and for the class MVBVS in [17].
Next, Tikhonov [13, 15, 16] and Leindler [9] defined the class of \(\beta \)—general monotone sequences as follows:
Definition 1
Let \(\beta :=\left( \beta _{n}\right) \) be a nonnegative sequence. The sequence of complex numbers \(a:=\left( a_{n}\right) \) is said to be \(\beta { -}\) general monotone, or \(a\in GM\left( \beta \right) \), if the relation
holds for all \(m \in \mathbb {N}\).
In the paper [15] Tikhonov considered i.e. the following examples of the sequences \(\beta _{n}\):
-
(1)
\(_{1}\beta _{n}=\left| a_{n}\right| ,\)
-
(2)
\(_{2}\beta _{n}=\sum \nolimits _{k=\left[ n/c \right] }^{\left[ cn\right] } \frac{\left| a_{k}\right| }{k}\) for some \(c>1\).
It is clear that \(GM\left( _{1}\beta \right) =GMS\). Moreover, Tikhonov showed in [15] that
Tikhonov proved also in [15] the following theorem:
Theorem 2
Let a sequence \((b_n) \in GM(_2\beta )\). If \(n|b_n| \rightarrow 0\) as \( n\rightarrow \infty \), then the series (1.1) converges uniformly.
Further, Szal defined a new class of sequences in the following way (see [11]):
Definition 2
Let \(\beta :=\left( \beta _{n}\right) \) be a nonnegative sequence and r a natural number. The sequence of complex numbers \(a:=\left( a_{n}\right) \) is said to be \(\left( \beta ,r\right) -\)general monotone, or \(a\in GM\left( \beta ,r\right) \), if the relation
holds for all \(m \in \mathbb {N}\).
It is clear that \(GM\left( \beta ,1\right) \equiv GM\left( \beta \right) \). Moreover, it is easy to show that the sequence
belongs to \(GM\left( {}_1\beta ,2\right) \) and does not belong to \(GM\left( {}_1\beta \right) \). This example shows that the class \(GM\left( {}_1\beta \right) \) is essentially wider than the class \(GM\left( {}_1\beta \right) \). In [11] Szal showed more general relations
for all \(r >1\).
In the paper [11] Szal generalized Theorem 1 by proving the following theorem.
Theorem 3
[11]. Let a sequence \(\left( b_{n}\right) \in GM\left( {}_2\beta ,r\right) \), where \(r \in \mathbb {N}\). If \(n|b_n| \rightarrow 0\) as \(n \rightarrow \infty \) and
then the series (1.1) converges uniformly.
In the paper [4] Kórus defined a new class of sequences in the following way:
Definition 3
The sequence of complex numbers \(a:=\left( a_{n}\right) \) is in the class \( SBVS_{2}\) (Supremum Bounded Variation Sequence), if the relation
holds for all \(m\in \mathbb {N}\), where (b(n)) is a nonnegative sequence tending monotonically to infinity depending only on a.
In the paper [4] Kórus also proved the following theorem:
Theorem 4
Let a sequence \((b_n) \in SBVS_2\). If \(n|b_n| \rightarrow 0\) as \( n\rightarrow \infty \), then the series (1.1) converges uniformly.
Next Tikhonov and Liflyand defined a class of \(GMS_p(\beta )\) in the following way (see [6, 7]):
Definition 4
Let \(\beta =(\beta _{n})\) be a nonnegative sequence and p a positive real number. We say that a sequence of complex numbers \(a=(a_{n})\in GMS_{p}(\beta )\) if the relation
holds for all \(m\in \mathbb {N}\).
It is clear that \(GMS_1(\beta )=GM(\beta )\).
The latest class of sequences was defined by Kubiak and Szal in [5] as follows:
Definition 5
Let \(\beta :=\left( \beta _{n}\right) \) be a nonnegative sequence, r a natural number and p a positive real number. The sequence of complex numbers \(a:=\left( a_{n}\right) \) is said to be \(\left( p,\beta ,r\right) -\) general monotone, or \(a\in GM\left( p, \beta ,r\right) \), if the relation
holds for all \(m\in \mathbb {N}\).
It is clear that \(GM(p,\beta ,1)=GMS_p(\beta )\) and \(GM(1,\beta ,r) = GM(\beta ,r)\).
Further we will consider the following sequence:
where \((a_n) \subset \mathbb {C}, a_n\rightarrow 0\) as \(n\rightarrow \infty \), \(q > 0\), (b(n)) is a nonnegative sequence such that \(b(n) \nearrow \) and \(b(n) \rightarrow \infty \) as \(n \rightarrow \infty \). It is clear that \(SBVS_2 = GM(1, {}_3\beta (1),1)\).
In the further part of our paper we will consider the following series:
where \(c >0.\)
In the paper [5] Kubiak and Szal showed the following embedding relations:
Theorem 5
Let \(q >0, r\in \mathbb {N}\) and \(0 < p_1 \le p_2\). Then
Theorem 6
Let \(p \ge 1\), \(q > 0\), \(r_1,r_2 \in \mathbb {N}\), \(r_1 \le r_2\). If \(r_1 \mid r_2\), then
Moreover they proved in [5] the following generalization of Theorem 1:
Theorem 7
Let a sequence \(\left( b_{n}\right) \in GM\left( p, {}_{3}\beta (q),r\right) \), where \(p,q\ge 1\), \(r \in \mathbb {N}\) and \(b(n)\ge n\) for \(n \in \mathbb {N}\). If
and
for all \(l= 1,...,[\frac{r}{2}]-1 \) when r is an even number and \(l= 1,...,[\frac{r}{2}] \) when r is an odd number, then the series (1.2) is uniformly convergent.
Theorem 8
Let a sequence \(\left( a_{n}\right) \in GM\left( p, {}_{3}\beta (q),r\right) \), where \(p,q\ge 1\), \(r \in \mathbb {N}\) and \(b(n)\ge n\) for \(n \in \mathbb {N}\). If
and
for all \(l= 0,1,...,[\frac{r}{2}] \), then the series (1.3) is uniformly convergent.
Theorem 9
Let a sequence \(\left( c_{n}\right) \in GM\left( p, {}_{3}\beta (q),r\right) \), where \(p,q\ge 1\), \(r \in \mathbb {N}\) and \(b(n)\ge n\) for \(n \in \mathbb {N}\). If
and
for all \(l= 0,1,...,[\frac{r}{2}] \), then the series (1.4) is uniformly convergent.
In this paper we will show that Theorems 7, 8, 9 are true under weakened assumptions in case \(p>1\).
2 Main Results
We have the following results:
Theorem 10
Let a sequence \(\left( b_{n}\right) \in GM\left( p, {}_{3}\beta (q),r\right) \), where \(q\ge 1\), \(p>1\) and \(r \in \mathbb {N}\). If
and
for all \(l= 1,...,[\frac{r}{2}]-1 \) when r is an even number and \(l= 1,...,[\frac{r}{2}] \) when r is an odd number, then the series (1.2) is uniformly convergent.
Proposition 1
There exist an \(x_0 \in \mathbb {R}\) and a sequence \( (b_n) \in GM(p, {}_3\beta (1), 3)\) for \(p>1\) with the properties \(nb_n \rightarrow 0 \) as \(n \rightarrow \infty \) and \((b_n) \notin GM(1, {}_3\beta (1),3)\), for which the series (1.2) is divergent in \(x_0\).
Theorem 11
Let a sequence \(\left( a_{n}\right) \in GM\left( p, {}_{3}\beta (q),r\right) \), where \(q\ge 1\), \(p>1\) and \(r \in \mathbb {N}\). If
and
for all \(l= 0,1,...,[\frac{r}{2}] \), then the series (1.3) is uniformly convergent.
Theorem 12
Let a sequence \(\left( c_{n}\right) \in GM\left( p, {}_{3}\beta (q),r\right) \), where \(q\ge 1\), \(p>1\) and \(r \in \mathbb {N}\). If
and
for all \(l= 0,1,...,[\frac{r}{2}] \), then the series (1.4) is uniformly convergent.
Remark 1
It is clear that if a sequence \((b_n)\) satisfies the condition (2.1) then it fulfills the condition (1.5) with \(p>1\), too. Therefore, from Theorem 10 we get Theorem 7 is case \(p>1\). The same remark applies to Theorems 11, 8 and Theorems 12, 9, respectively.
3 Lemma
Denote, for \(r \in \mathbb {N}\) and \(k=0,1,2...\) by
the Dirichlet type kernels.
Lemma 1
. [11, 12] Let \(r,m,n \in \mathbb {N}, l\in \mathbb {Z}\) and \((a_k) \subset \mathbb {C}\). If \(x \ne \frac{2l\pi }{r}\), then for \(m \ge n\)
and
Lemma 2
[5]. Let \(r,m,n\in \mathbb {N}, l \in \mathbb {Z}\) and \(a=(a_n) \subset \mathbb {C}\). If \(x \ne \frac{2l\pi }{r}\), then for \(m \ge n\)
Lemma 3
Let \(n, N \in \mathbb {N}\). Then for \( p \ge 1\)
Proof
This inequality is true for \(p =1 \). Consider the function
for \(p > 0\). We get:
It means that the function is non-decresing with respect to p. Thus:
Hence we get that:
Therefore, integrating by substitution with \(\ln k = t\) and using (3.3), we get
and the proof is completed. \(\square \)
4 Proofs of the Main Results
4.1 Proof of the Theorem 10
Let \(\epsilon >0\). Then from (2.1) and (2.2) we obtain:
and
for all \(n > N_\epsilon \) and \(N \in \mathbb {N}\), where \(l= 1,...,[\frac{r}{2} ]-1 \) when r is an even number and \(l= 1,...,[\frac{r}{2}] \) when r is an odd number. Denote by
We will show that
holds for any \(n\ge \max \{N_\varepsilon ,2\}\) and \(x \in \mathbb {R}\). Since \( \tau _{n}\left( 0 \right) =0\) and \(\tau _{n}\left( \frac{\pi }{c} \right) =0\) it suffices to prove (4.4) for \(0<x< \frac{\pi }{c} \).
First, we will show that (4.4) is valid for \(x=\frac{2\,l\pi }{rc}\), where l is an integer number such that \(0<2\,l<r.\) Using (4.2) we get
Now, we prove that (4.4) holds for \(\frac{2\,l\pi }{rc}<x\le \frac{ 2\,l\pi }{rc}+\frac{\pi }{rc}\), where \(0\le 2\,l<r\).
Let \(N^{\frac{1}{p}}:=N^{\frac{1}{p}}\left( x\right) \ge r \) be a natural number such that
Then
Applying Lagrange’s mean value theorem to the function \(f\left( x\right) =\sin (ckx)\) on the interval \(\left[ \frac{2\,l\pi }{rc},x\right] \) we obtain that for each k there exists \(y_k\in \left( \frac{2\,l\pi }{rc},x\right) \) such that
Using this we get
From (4.3) we have
Using Lemma 3 we obtain
If \(\left( b_{n}\right) \in GM\left( p,{}_3\beta (q),r\right) \), then using Lemma 1, we get
Further applying the Hölder inequality with \(p>1\), the inequality \( \frac{rc}{\pi }x-2\,l\le \left| \sin \frac{rcx}{2}\right| \) \(\left( x\in \left[ \frac{2\,l\pi }{rc },\frac{2\,l\pi }{rc}+\frac{\pi }{rc}\right] \text { and }0\le 2\,l<r\right) \), (4.5) and (4.1), we obtain
Elementary calculations give:
Finally, we prove that (4.4) is true for \(\frac{2\,l\pi }{rc}+\frac{\pi }{rc }\le x<\frac{2\left( l+1\right) \pi }{rc}\), where \(0<2\left( l+1\right) \le r.\)
Let \(M^{\frac{1}{p}}:=M^{\frac{1}{p}}\left( x\right) \ge r\) be a natural number such that
Then
Applying Lagrange’s mean value theorem to the function \(f\left( x\right) =\sin (ckx)\) on the interval \(\left[ x,\frac{2\left( l+1\right) \pi }{rc} \right] \) we obtain that for each k there exists \(z_k\in \left( x,\frac{ 2\left( l+1\right) \pi }{rc }\right) \) such that
Using this we get
From (4.2) we have
Using Lemma 3 we get
If \(\left( b_{n}\right) \in GM\left( p,{}_{3}\beta (q),r\right) \), then by Lemma 1
Next, applying the Hölder inequality with \(p>1\), then using Lemma 1, the inequality
\(2\left( l+1\right) -\frac{rc}{\pi }x\le \left| \sin \frac{rcx}{2} \right| \) \(\left( x\in \left[ \frac{2\,l\pi }{rc}+\frac{\pi }{rc},\frac{ 2\left( l+1\right) \pi }{rc}\right] \text { and }0<2\left( l+1\right) \le r\right) \), (4.6) and (4.1), we get
Elementary calculations give
Joining the obtained estimates the uniform convergence of series (1.2) follows and thus the proof is complete. \(\square \)
4.2 Proof of Proposition 1
Let for \(n \in \mathbb {N}\):
\(a_n =\left\{ \begin{array}{l} \frac{3}{n\ln (n+1)},\text { when } n=1\text { (mod }3), \\ \frac{1}{n\ln (n+1)},\text { when } n=2\text { (mod }3), \\ \frac{1}{n\ln (n+1)},\text { when } n=0\text { (mod }3) \text { and } n\ne 0 \text { (mod }6), \\ \frac{1}{(n-3)\ln (n-2)} + \frac{1}{n^{1+\frac{1}{p}}\ln (n+1)},\text { when } n=0\text { (mod }6). \end{array} \right. \)
First, we prove that \((a_{n})\in GM(p,{}_{3}\beta (1),3)\) for \(p>1\). Let
Using elementary calculations we get
Moreover
for \(k\ge 1\) and
for \(k\ge 6\). Thus
Hence \((a_{n})\in GM(p,{}_{3}\beta (1),3)\). Now, we will show that \( (a_{n})\notin GM(1,{}_{3}\beta (1),3)\). We have
On the other hand, we get
Therefore, the inequality
can not be satisfied if \(n\rightarrow \infty \).
Now, we will show that the series (1.2) is divergent in \(x_0 = \frac{ 2}{3}\pi \). We have
This ends our proof. \(\square \)
4.3 Proof of Theorem 11
The proof is similar to the proof of Theorem 10. The only difference is that we use (2.3) and (3.2) instead of (2.2) and (3.1), respectively. \(\square \)
4.4 Proof of Theorem 12
The proof is similar to the proof of Theorem 10. The only difference is that we use (2.4) and Lemma 2 instead of (3.1) and Lemma 1, respectively. \(\square \)
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
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Kubiak, M., Szal, B. A Sufficient Condition for Uniform Convergence of Trigonometric Series with p-Bounded Variation Coefficients. Results Math 78, 236 (2023). https://doi.org/10.1007/s00025-023-02011-4
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DOI: https://doi.org/10.1007/s00025-023-02011-4
Keywords
- Sine series
- Cosine series
- Trigonometric series
- Embedding relations
- Number sequences
- p-bounded variation sequences