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Generalized Vector-Valued Sequence Spaces Defined by Modulus Functions
Journal of Inequalities and Applications volume 2010, Article number: 457892 (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.
Let be a sequence of seminormed spaces such that
for each
. We define

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
(i) if and only if
,
(ii) for
,
(iii) is increasing,
(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.
The notion of difference sequence spaces was introduced by Kızmaz [17] and it was generalized by Et and Çolak [18]. Let be a fixed positive integer. Then we write

for ,
and
, where
,
,
and so we have

2. Main Results
In this section, we prove some results involving the sequence spaces ,
, and
.
Definition 2.1.
Let be a sequence of seminormed spaces such that
for each
,
a sequence of strictly positive real numbers,
a sequence of seminorms,
a sequence of modulus functions, and
any fixed sequence of nonzero complex numbers
. We define the following sequence spaces:

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.
Let be a modulus function and the sequence
be bounded; then

and the inclusions are strict.
Theorem 2.4.

is a paranormed (need not total paranorm) space with

where .
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
(i);
(ii);
(iii);
(iv)If is stronger than
for each
, then
;
(v)If equivalent to
for each
, then
;
(vi).
Proof.
-
(i)
We will only prove (i) for
and the other cases can be proved by using similar arguments. Let
and choose
with
such that
for
and for all
. Write
and consider
(2.4)
where the first summation is over and second summation is over
. Since
is continuous, we have

By the definition of , we have for
,

Hence

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.
Let and
be bounded; then
.
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.
A subset of
is said to have density positive integers which is defined by
if

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.
A sequence is said to be
-statistically convergent to
if for every
,

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
(i)If , then
;
(ii)If and
, then
;
(iii),
where .
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.
Let and let
be given. Let
and
denote the sums over
with
and
, respectively. Then

Hence .
Theorem 3.4.
Let be bounded; then
.
Proof.
Suppose that is bounded. Let
and
and
be denoted in previous theorem. Since
is bounded, there exists an integer
such that
, for all
. Then

Hence .
Theorem 3.5.

if and only if is bounded.
Proof.
Let be bounded. By Theorems 3.3 and 3.4, we have
.
Conversely suppose that is unbounded. Then there exists a sequence
of positive numbers with
, for
. If we choose

then we have

for all and so
, but
for
,
and
for all
. This contradicts to
.
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Işik, M. Generalized Vector-Valued Sequence Spaces Defined by Modulus Functions. J Inequal Appl 2010, 457892 (2010). https://doi.org/10.1155/2010/457892
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DOI: https://doi.org/10.1155/2010/457892
Keywords
- Positive Integer
- Real Number
- Complex Number
- Similar Argument
- Standard Technique