# Generalized Vector-Valued Sequence Spaces Defined by Modulus Functions

- Mahmut Işik
^{1}Email author

**2010**:457892

https://doi.org/10.1155/2010/457892

© Mahmut Işik. 2010

**Received: **17 June 2010

**Accepted: **16 December 2010

**Published: **21 December 2010

## Abstract

We introduce the vector-valued sequence spaces , , and , and , using a sequence of modulus functions and the multiplier sequence of nonzero complex numbers. We give some relations related to these sequence spaces. It is also shown that if a sequence is strongly -Cesàro summable with respect to the modulus function then it is -statistically convergent.

## 1. Introduction

Let
be the set of all sequences real or complex numbers and
,
, and
be, respectively, the Banach spaces of *bounded*, *convergent,* and *null sequences*
with the usual norm
, where
, the set of positive integers.

The studies on vector-valued sequence spaces are done by Das and Choudhury [1], Et [2], Et et al. [3], Leonard [4], Rath and Srivastava [5], J. K. Srivastava and B. K. Srivastava [6], Tripathy et al. [7, 8], and many others.

It is easy to verify that is a linear space under usual coordinatewise operations defined by and , where .

Let be a sequences of nonzero scalar. Then for a sequence space , the multiplier sequence space , associated with the multiplier sequence , is defined as .

The notion of a modulus was introduced by Nakano [9]. We recall that a modulus is a function from to such that

(iv) is continuous from the right at 0.

It follows that must be continuous everywhere on . Maddox [10] and Ruckle [11] used a modulus function to construct some sequence spaces.

After then some sequence spaces defined by a modulus function were introduced and studied by Bilgin [12], Pehlivan and Fisher [13], Waszak [14], Bhardwaj [15], Altın [16], and many others.

## 2. Main Results

In this section, we prove some results involving the sequence spaces , , and .

Definition 2.1.

Throughout the paper will denote any one of the notation 0,1 or .

If and for all , we will write instead of .

If and for all , we will write instead of .

If , we say that is strongly -Cesàro summable with respect to the modulus function and we will write and will be called -limit of with respect to the modulus .

The proofs of the following theorems are obtained by using the known standard techniques; therefore, we give them without proofs.

Theorem 2.2.

Let the sequence be bounded. Then the spaces are linear spaces.

Theorem 2.3.

and the inclusions are strict.

Theorem 2.4.

Theorem 2.5.

Let and be any two sequences of modulus functions. For any bounded sequences and of strictly positive real numbers and for any two sequences of seminorms and , we have

(iv)If is stronger than for each , then ;

(v)If equivalent to for each , then ;

- (i)

From (2.5) and (2.7), we obtain .

The following result is a consequence of Theorem 2.5(i).

Corollary 2.6.

Let be a modulus function. Then .

Theorem 2.7.

Proof.

If we take for all and using the same technique of Theorem 5 of Maddox [19], it is easy to prove the theorem.

Theorem 2.8.

Let be a modulus function; if , then .

Proof.

Omitted.

## 3. -Statistical Convergence

The notion of statistical convergence were introduced by Fast [20] and Schoenberg [21], independently. Over the years and under different names, statistical convergence has been discussed in the theory of Fourier analysis, ergodic theory, and number theory. Later on it was further investigated from the sequence space point of view and linked with summability theory by Šalát [22], Fridy [23], Connor [24], Mursaleen [25], Işik [26], Malkowsky and Sava [27], and many others. In recent years, generalizations of statistical convergence have appeared in the study of strong integral summability and the structure of ideals of bounded continuous functions on locally compact spaces. Statistical convergence and its generalizations are also connected with subsets of the Stone-Čech compactification of the natural numbers. Moreover, statistical convergence is closely related to the concept of convergence in probability. The notion depends on the density of subsets of the set of natural numbers.

where is the characteristic function of . It is clear that any finite subset of have zero natural density and .

In this section, we introduce -statistically convergent sequences and give some inclusion relations between -statistically convergent sequences and -summable sequences.

Definition 3.1.

In this case, we write . The set of all -statistically convergent sequences is denoted by . In the case , we will write instead of .

Theorem 3.2.

Let be a modulus function; then

Proof.

Omitted.

In the following theorems, we will assume that the sequence
is bounded and
*.*

Theorem 3.3.

Let be a modulus function. Then .

Proof.

Theorem 3.4.

Proof.

Theorem 3.5.

Proof.

Let be bounded. By Theorems 3.3 and 3.4, we have .

for all and so , but for , and for all . This contradicts to .

## Authors’ Affiliations

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## Copyright

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