Abstract
The aim of this paper is to introduce the normed binomial sequence spaces by combining the binomial transformation and difference operator, where . We prove that these spaces are linearly isomorphic to the spaces and , respectively. Furthermore, we compute Schauder bases and the α-, β- and γ-duals of these sequence spaces.
Keywords: sequence space; matrix domain; Schauder basis; α-, β- and γ-duals
Introduction and preliminaries
Let w denote the space of all sequences. By , , c and , we denote the spaces of p-absolutely summable, bounded, convergent and null sequences, respectively, where . Let Z be a sequence space, then Kizmaz [1] introduced the following difference sequence spaces:
for , where for each , the set of positive integers. Since then, many authors have studied further generalization of the difference sequence spaces [2–6]. Moreover, Altay and Polat [7], Başarir and Kara [8–12], Kara [13], Kara and İlkhan [14], Polat and Başar [15], and many others have studied new sequence spaces from a matrix point of view that represent difference operators.
For an infinite matrix and , the A-transform of x is defined by and is supposed to be convergent for all , where . For two sequence spaces X, Y and an infinite matrix , the sequence space is defined by , which is called the domain of matrix A in the space X. By , we denote the class of all matrices such that .
The Euler means of order r is defined by the matrix , where and
The Euler sequence spaces and were defined by Altay, Başar and Mursaleen [16] as follows:
and
Altay and Polat [7] defined further generalization of the Euler sequence spaces , and by
and
where for each . Here any term with negative subscript is equal to naught. Many authors have used especially the Euler matrix for defining new sequence spaces, for instance, Kara and Başarir [17], Karakaya and Polat [18] and Polat and Başar [15].
Recently Bişgin [19, 20] defined another type of generalization of the Euler sequence spaces and introduced the binomial sequence spaces , , and . Let and . Then the binomial matrix is defined by
for all . For we have
-
(i)
,
-
(ii)
for each ,
-
(iii)
.
Thus, the binomial matrix is regular for . Unless stated otherwise, we assume that . If we take , we obtain the Euler matrix . So the binomial matrix generalizes the Euler matrix. Bişgin [20] defined the following spaces of binomial sequences:
and
The main purpose of the present paper is to study the normed difference spaces and of the binomial sequence whose -transforms are in the spaces and , respectively. These new sequence spaces are the generalization of the sequence spaces defined in [7] and [20]. Also, we compute the bases and α-, β- and γ-duals of these sequence spaces.
The binomial difference sequence spaces
In this section, we introduce the spaces and and prove that these sequence spaces are linearly isomorphic to the spaces and , respectively.
We first define the binomial difference sequence spaces and by
and
Let us define the sequence as the -transform of a sequence , that is,
| 2.1 |
for each . Then the binomial difference sequence spaces or can be redefined by all sequences whose -transforms are in the space or .
Theorem 2.1
The sequence spaces and are complete linear metric spaces with the norm defined by
and
where and the sequence is defined by the -transform of x.
Proof
The proof of the linearity is a routine verification. It is obvious that and if and only if for all , where θ is the zero element in and . We consider , then we have
Hence is a norm on the space .
Let be a Cauchy sequence in , where for each . For every , there is a positive integer such that . Then we get
for and each . So is a Cauchy sequence in the set of real numbers . Since is complete, we have for each . We compute
| 2.2 |
for . We take i and l →∞, then the inequality (2.2) implies that
We have
that is, . Thus, the space is complete. For the space , the proof can be completed in a similar way. So, we omit the detail. □
Theorem 2.2
The sequence spaces and are linearly isomorphic to the spaces and , respectively, where .
Proof
Similarly, we only prove the theorem for the space . To prove , we must show the existence of a linear bijection between the spaces and .
Consider by . The linearity of T is obvious and whenever . Therefore, T is injective.
Let and define the sequence by
| 2.3 |
for each . Then we have
which implies that and . Consequently, T is surjective and is norm preserving. Thus, . □
The Schauder basis and α-, β- and γ-duals
For a normed space , a sequence is called a Schauder basis [21] if for every , there is a unique scalar sequence such that . Next, we shall give a Schauder basis for the sequence space .
We define the sequence by
for each .
Theorem 3.1
The sequence is a Schauder basis for the binomial sequence spaces and every has a unique representation by
| 3.1 |
where and for each .
Proof
Obviously, , where is the sequence with 1 in the kth place and zeros elsewhere for each . This implies that for each .
For and , we put
By the linearity of , we have
and
for each .
For any given , there is a positive integer such that
for all . Then we have
which implies that is represented as (3.1).
To prove the uniqueness of this representation, we assume that
Then we have
which is a contradiction with the assumption that for each . This shows the uniqueness of this representation. □
Corollary 3.2
The sequence space is separable, where .
For the duality theory, the study of sequence spaces is more useful when we investigate them equipped with linear topologies. Köthe and Toeplitz [22] first computed duals whose elements can be represented as sequences and defined the α-dual (or Köthe-Toeplitz dual).
For the sequence spaces X and Y, define the multiplier space by
Then the α-, β- and γ-duals of a sequence space X are defined by
respectively.
We give the following properties:
| 3.2 |
| 3.3 |
| 3.4 |
| 3.5 |
| 3.6 |
| 3.7 |
where Γ is the collection of all finite subsets of , and .
Lemma 3.3
[23]
Let be an infinite matrix. Then the following statements hold:
Theorem 3.4
We define the set and by
and
Then and , where .
Proof
Let and be defined by (2.3), then we have
for each , where is defined by
Therefore, we deduce that whenever or if and only if whenever or , which implies that if and only if and by parts (i) and (iv) of Lemma 3.3, we obtain if and only if
and if and only if
Thus, we have and , where . □
Now, we define the sets , , , and by
and
Theorem 3.5
We have the following relations:
-
(i)
,
-
(ii)
, where ,
-
(iii)
,
-
(iv)
,
-
(v)
, where ,
-
(vi)
.
Proof
Let and be defined by (2.3), then we consider the following equation:
where is defined by
Therefore, we deduce that whenever if and only if whenever , which implies that if and only if . By Lemma 3.3(ii), we obtain . Using Lemma 3.3(i) and (iii)-(viii) instead of (ii), the proof can be completed in a similar way. So, we omit the details. □
Conclusion
By considering the definitions of the binomial matrix and the difference operator, we introduce the sequence spaces and . These spaces are the natural continuations of [1, 7, 20]. Our results are the generalizations of the matrix domain of the Euler matrix of order r. In order to give fully inform the reader on related topics with applications and a possible line of further investigation, the e-book [24] is added to the list of references.
Acknowledgements
We wish to thank the referee for his/her constructive comments and suggestions.
Footnotes
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
JM came up with the main ideas and drafted the manuscript. MS revised the paper. All authors read and approved the final manuscript.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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