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An Orlicz extension of difference sequences on real linear n-normed spaces

Abstract

In this paper, we present an extension of some classes of difference sequences by considering them in a base space X, a real linear n-normed space via a sequence of Orlicz functions. We investigate the spaces for linearity, existence of norms and completeness under different conditions. We also show that they are convex spaces and compute their topologically equivalent spaces. Further some results on equivalence of various norms on such extended spaces are presented.

MSC:40A05, 46B20, 46B99, 46A19, 46A99.

1 Introduction and preliminaries

Let w denote the space of all real or complex sequences. By c, c 0 and , we denote the Banach spaces of convergent, null and bounded sequences x=( x k ), respectively, normed by

x= sup k | x k |.

An Orlicz function is a function M:[0,)[0,) which is continuous, non-decreasing and convex with M(0)=0, M(x)>0 for x>0 and M(x) as x.

Lindenstrauss and Tzafriri [1] used the Orlicz function and introduced the sequence space M as follows:

M = { ( x k ) w : k = 1 M ( | x k | ρ ) <  for some  ρ > 0 } .

They proved that M is a Banach space normed by

x=inf { ρ > 0 : k = 1 M ( | x k | ρ ) 1 } .

The study of Orlicz sequence spaces was initiated with a certain specific purpose in Banach space theory. Indeed, Lindberg got interested in Orlicz spaces in connection with finding Banach spaces with symmetric Schauder bases having complementary subspaces isomorphic to c 0 or p (1p<). Subsequently, Lindenstrauss and Tzafriri [1] studied these Orlicz sequence spaces in more detail, and solved many important and interesting structural problems in Banach spaces. Later on, different classes of sequence spaces defined by an Orlicz function were studied by different authors. For details, one may refer to Kamthan and Gupta [2].

The notion of a difference sequence space was introduced by Kizmaz [3] who studied the difference sequence spaces (Δ), c(Δ) and c 0 (Δ). The notion was further generalized by Et and Colak [4] by introducing the spaces ( Δ s ), c( Δ s ) and c 0 ( Δ s ). Another type of generalization of the difference sequence spaces is due to Tripathy and Esi [5] who studied the spaces ( Δ m ), c( Δ m ) and c 0 ( Δ m ). Tripathy et al. [6] generalized the above notions and unified these as follows.

Let m, s be non-negative integers. Then, for a given sequence space Z, we have

Z ( Δ m s ) = { x = ( x k ) w : ( Δ m s x k ) Z } ,

where Δ m s x=( Δ m s x k )=( Δ m s 1 x k Δ m s 1 x k + m ) and Δ m 0 x k = x k for all kN, which is equivalent to the following binomial representation:

Δ m s x k = υ = 0 s ( 1 ) υ ( s υ ) x k + m υ .

Taking m=1, we get the spaces ( Δ s ), c( Δ s ) and c 0 ( Δ s ) studied by Et and Colak [4]. Taking s=1, we get the spaces ( Δ m ), c( Δ m ) and c 0 ( Δ m ) studied by Tripathy and Esi [5]. Taking m=s=1, we get the spaces (Δ), c(Δ) and c 0 (Δ) introduced and studied by Kizmaz [3].

Let m, s be non-negative integers. Then, for a given sequence space Z, Dutta [7] introduced the following spaces:

Z ( Δ ( s ) m ) = { x = ( x k ) w : ( Δ ( s ) m x k ) Z } ,

where Δ ( s ) m x=( Δ ( s ) m x k )=( Δ ( s ) m 1 x k Δ ( s ) m 1 x k s ) and Δ ( s ) 0 x k = x k for all kN, which is equivalent to the following binomial representation:

Δ ( s ) m x k = v = 0 m ( 1 ) v ( m v ) x k s v .

The concept of 2-normed spaces was introduced and studied by Gähler, a German Mathematician who worked at German Academy of Science, Berlin, in a series of papers in the German language published in Mathematische Nachrichten; see, for example, references [813]. This notion, which is nothing but a two-dimensional analogue of a normed space, got the attention of a wider audience after the publication of a paper by White [14] in 1969 entitled 2-Banach spaces. In the same year Gähler published another paper on this theme in the same journal. Siddiqi delivered a series of lectures on this theme in various conferences in India and Iran. His joint paper with Gähler and Gupta [15] of 1975 also provided valuable results related to the theme of this paper. The notion of n-normed spaces can be found in Misiak [16]. Since then, many others have studied this concept and obtained various results; see, for instance, Gunawan [17, 18], Gunawan and Mashadi [8, 19], Dutta [2022] and Gürdal et al. [23]. For some related and recent works in this area, one may refer to Chu and Ku [24] and Tanaka and Saito [25].

Let nN and X be a real vector space of dimension d, where nd. A real-valued function ,, on X n satisfying the following four conditions:

(N1) x 1 , x 2 ,, x n =0 if and only if x 1 , x 2 ,, x n are linearly dependent,

(N2) x 1 , x 2 ,, x n is invariant under permutation,

(N3) α x 1 , x 2 ,, x n =|α| x 1 , x 2 ,, x n for any αR,

(N4) x+ x , x 2 ,, x n x, x 2 ,, x n + x , x 2 ,, x n is called an n-norm on X, and the pair (X,,,) is called an n-normed space.

A trivial example of an n-normed space is X= R n equipped with the following Euclidean n-norm:

x 1 , x 2 , , x n E =abs ( | x 11 x 1 n x n 1 x n n | ) ,

where x i =( x i 1 ,, x i n ) R n for each i=1,2,,n.

If (X,,,) is an n-normed space of dimension dn2 and { a 1 , a 2 ,, a n } is a linearly independent set in X, then the following function , , on X n 1 defined by

x 1 , x 2 , , x n 1 =max { x 1 , x 2 , , x n 1 , a i : i = 1 , 2 , , n }
(1.1)

defines an (n1)-norm on X with respect to { a 1 , a 2 ,, a n }, and this is known as derived (n1)-norm on X.

The standard n-norm on X, which is a real inner product space of dimension dn, is given as follows:

x 1 , , x n S = | x 1 , x 1 x 1 , x n x n , x 1 x n , x n | 1 2 ,

where , denotes the inner product on X. If X= R n , then this n-norm is exactly the same as the Euclidean n-norm x 1 , x 2 , , x n E mentioned earlier. For n=1, this n-norm is the usual norm x 1 = x 1 , x 1 1 2 .

A sequence ( x k ) in an n-normed space (X,,,) is said to converge to some LX in the n-norm if

lim k x k L, u 2 ,, u n =0for every  u 2 ,, u n X.

A sequence ( x k ) in an n-normed space (X,,,) is said to be Cauchy with respect to the n-norm if

lim k , l x k x l , u 2 ,, u n =0for every  u 2 ,, u n X.

If every Cauchy sequence in X converges to some LX, then X is said to be complete with respect to the n-norm. Any complete n-normed space is said to be an n-Banach space.

Now we state the following useful results on the n-norm as lemmas which were given in [26].

Lemma 1.1 Every n-normed space is an (nr)-normed space for all r=1,2,,n1. In particular, every n-normed space is a normed space.

Lemma 1.2 A standard n-normed space is complete if and only if it is complete with respect to the usual norm S = , 1 2 .

Lemma 1.3 On a standard n-normed space X, the derived (n1)-norm , , , defined with respect to an orthonormal set { e 1 , e 2 ,, e n }, is equivalent to the standard (n1)-norm , , S . Precisely, we have

x 1 , , x n 1 x 1 , , x n 1 S n x 1 , , x n 1

for all x 1 ,, x n 1 , where x 1 , , x n 1 =max{ x 1 , , x n 1 , e i S :i=1,,n}.

Let (X, , , X ) be a real linear n-normed space and let w(X) denote an X-valued sequence space. Then, for a sequence of Orlicz functions M=( M k ), we define the following difference sequence spaces:

c 0 ( X , M , Δ ( s ) m ) = { ( x k ) w ( X ) : lim k M k ( Δ ( s ) m x k ρ , z 1 , , z n 1 X ) = 0 for every non-zero  z 1 , , z n 1 X  and for some  ρ > 0 } , c ( X , M , Δ ( s ) m ) = { ( x k ) w ( X ) : lim k M k ( Δ ( s ) m x k ρ L , z 1 , , z n 1 X ) = 0 for every non-zero  z 1 , , z n 1 X  and for some  L X , ρ > 0 } , ( X , M , Δ ( s ) m ) = { ( x k ) w ( X ) : sup k M k ( Δ ( s ) m x k ρ , z 1 , , z n 1 X ) < for every non-zero  z 1 , , z n 1 X  and for some  ρ > 0 } .

Similarly, we can define c 0 (X,M, Δ s m ), c(X,M, Δ s m ) and (X,M, Δ s m ).

In the above definition of spaces, the n-norm , , X on X is either a standard n-norm or a non-standard n-norm. In general, we write , , X , and for a standard case, we write , , S . For a derived norm, we use , , .

It is obvious that c 0 (X,M, Δ ( s ) m )c(X,M, Δ ( s ) m ). Again, c(X,M, Δ ( s ) m ) (X,M, Δ ( s ) m ) follows from the following inequality:

M k ( Δ ( s ) m x k 2 ρ , z 1 , , z n 1 X ) 1 2 M k ( Δ ( s ) m x k L ρ , z 1 , , z n 1 X ) + 1 2 M k ( L ρ , z 1 , , z n 1 X ) .

Similarly, we have c 0 (X,M, Δ s m )c(X,M, Δ s m ) (X,M, Δ s m ). Also, it is obvious that for Z=c, c 0  and  , Z(X,M, Δ s i )Z(X,M, Δ s m ), i=0,1,,m1 and Z(X,M, Δ ( s ) i )Z(X,M, Δ ( s ) m ), i=0,1,,m1.

When X=R, m=1, s=0 and M k (x)=|x| for all x[0,) and k1, the above spaces deduce to the famous and very useful spaces c, c 0 and .

2 Main results

In this section we investigate some results on the n-norm as well as the main results of this article involving the sequence spaces c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ), (X,M, Δ ( s ) m ), c 0 (X,M, Δ s m ), c(X,M, Δ s m ) and (X,M, Δ s m ).

The proofs of the following two propositions are easy and so they are omitted.

Proposition 2.1 Let nN and X be a real vector space of dimension d, where 2nd. Let β n 1 be the collection of linearly independent sets B with n1 elements. For B β n 1 , let us define

p B ( x 1 )= x 1 , x 2 ,, x n , x 1 X.

Then p B is a seminorm on X and the family P={ p B :B β n 1 } of seminorms generates a locally convex topology on X.

Proposition 2.2 The seminorms p B ’s have the following properties:

  1. (i)

    ker( p B )= linear span of B,

  2. (ii)

    for B β n 1 , yB and xX linear span of B, we have

    p B { x } y (y)= p B (x).

Hence we have the following proposition.

Proposition 2.3 The seminorms defined by Proposition  2.1 satisfy the axiom of an n-norm.

Example 2.1 Consider the linear space P m of real polynomials of degree ≤m on the interval [0,1]. Let { x i } i = 0 n m be nm+1 arbitrary but distinct fixed points in [0,1]. For f 1 , f 2 ,, f n in P m , let us define

f 1 , f 2 ,, f n ={ 0 , if  f 1 , f 2 , , f n  are linearly dependent , i = 0 n m | f 1 ( x i ) f 2 ( x i ) f n ( x i ) | , if  f 1 , f 2 , , f n  are linearly independent .

Then ,, is an n-norm on P m .

Proof The proof is a routine verification and so it is omitted. □

Theorem 2.1 The spaces c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ), (X,M, Δ ( s ) m ), c 0 (X,M, Δ s m ), c(X,M, Δ s m ) and (X,M, Δ s m ) are linear.

Proof The proof is a routine verification and thus it is omitted. □

Theorem 2.2 (i) c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ) are normed linear spaces by

x ( s ) 0 =inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ , z 1 , , z n 1 X ) 1 } ,
(2.1)
  1. (ii)

    c 0 (X,M, Δ s m ), c(X,M, Δ s m ) and (X,M, Δ s m ) are normed linear spaces by

    x s 0 = k = 1 m s x k +inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ s m x k ρ , z 1 , , z n 1 X ) 1 } ,
    (2.2)

where is the derived 1-norm (norm) on X.

Proof (i) If x=θ, then clearly x ( s ) 0 =0. Conversely, assume x ( s ) 0 =0. Then using (2.1), we have

inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ , z 1 , , z n 1 X ) 1 } =0.

This implies that for a given ε>0, there exists some ρ ε (0< ρ ε <ε) such that

sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ ε , z 1 , , z n 1 X ) 1.

So,

M k ( Δ ( s ) m x k ρ ε , z 1 , , z n 1 X ) 1for every  z 1 ,, z n 1 X and k1.

Hence, for every z 1 ,, z n 1 X,

M k ( Δ ( s ) m x k ε , z 1 , , z n 1 X ) M k ( Δ ( s ) m x k ρ ε , z 1 , , z n 1 X ) 1for every k1.

Suppose Δ ( s ) m x n i 0 for some i. Let ε0, then Δ ( s ) m x n i ε , z 1 , , z n 1 X .

It follows that M k ( Δ ( s ) m x n i ε , z 1 , , z n 1 X ) as ε0 for some n i N. This is a contradiction.

So, we must have Δ ( s ) m x k =0 for all k1. Let k=1, then Δ ( s ) m x 1 = v = 0 m ( 1 ) v ( m v ) x 1 s v =0 and so x 1 =0, by taking x 1 s v =0, for v=1,,m. Thus, taking k=2,,ms, , we can easily conclude that x k =0 for all k1.

Thus x=θ.

Let x=( x k ) and y=( y k ) be any two elements. Then there exist ρ 1 , ρ 2 >0 such that

sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ 1 , z 1 , , z n 1 X ) 1

and

sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m y k ρ 2 , z 1 , , z n 1 X ) 1.

Let ρ= ρ 1 + ρ 2 . Then, by the convexity of M, we have

sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k + y k ) ρ , z 1 , , z n 1 X ) ( ρ 1 ρ 1 + ρ 2 ) sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ 1 , z 1 , , z n 1 X ) + ( ρ 2 ρ 1 + ρ 2 ) sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m y k ρ 2 , z 1 , , z n 1 X ) 1 .

Now

x + y ( s ) 0 = inf { ρ : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k + y k ) ρ , z 1 , , z n 1 X ) 1 } inf { ρ 1 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ 1 , z 1 , , z n 1 X ) 1 } + inf { ρ 2 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m y k ρ 2 , z 1 , , z n 1 X ) 1 } .

Thus

x + y ( s ) 0 x ( s ) 0 + y ( s ) 0 .

Finally, let α be any scalar. Then

α x ( s ) 0 = inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m α x k ρ , z 1 , , z n 1 X ) 1 } = inf { ( | α | λ ) > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k λ , z 1 , , z n 1 X ) 1 } = | α | x ( s ) 0 ,

where λ= ρ | α | .

This completes the proof.

  1. (ii)

    The proof follows by applying similar arguments as above. □

Remark It is obvious that ( x k )Z(X,M, Δ ( s ) m ) if and only if ( x k )Z(X,M, Δ s m ) for Z=c, c 0  and  . Moreover, it is clear that the norms ( s ) 0 and s 0 are equivalent.

Theorem 2.3 (i) The spaces c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ) are topologically isomorphic with the spaces c 0 (X,M), c(X,M) and (X,M), respectively.

  1. (ii)

    The spaces S c 0 (X,M, Δ s m ), Sc(X,M, Δ s m ) and S (X,M, Δ s m ) are topologically isomorphic with the spaces c 0 (X,M), c(X,M) and (X,M), respectively, where SZ(X,M, Δ s m )={x=( x k ):xZ(X,M, Δ s m ), x 1 = x 2 == x m s =0} is a subspace of Z(X, Δ s m ), Z=c, c 0 and .

  2. (iii)

    c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ), (X,M, Δ ( s ) m ), c 0 (X,M, Δ s m ), c(X,M, Δ s m ) and (X,M, Δ s m ) are convex sets.

Proof (i) For Z=c, c 0  and  , let us consider the mapping T:Z(X,M, Δ ( s ) m )Z(X,M), defined by

Tx=y= ( Δ ( s ) m x k ) for every x=( x k )Z ( X , M , Δ ( s ) m ) .

Clearly T is linear homeomorphism.

  1. (ii)

    In this case we consider the mapping T :SZ(X,M, Δ s m )Z(X,M), defined by

    T x=y= ( Δ s m x k ) for every x=( x k )SZ ( X , M , Δ s m ) .

Clearly T is a linear homeomorphism.

  1. (iii)

    The proof follows by using the convexity of Orlicz functions. □

Remark Let { a 1 , a 2 ,, a n } be a linearly independent set in X. Then Δ ( s ) m x k , z 1 , , z n r 1 =max{ Δ ( s ) m x k , z 1 , , z n r 1 , a i 1 , , a i r X }, { i 1 ,, i r }{1,,n} is a derived (nr)-norm on X for each r=1,,n1 and for each k1.

Hence we have the following theorem.

Theorem 2.4 Let { a 1 , a 2 ,, a n } be any linearly independent set in X. Then c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ) are normed linear spaces by

x ( s ) r = inf { ρ > 0 : sup k 1 , z 1 , , z n r 1 X M k ( Δ ( s ) m x k ρ , z 1 , , z n r 1 ) 1 } for each r = 1 , , n 1 .
(2.3)

We call these norms derived norms.

Proof Proof is similar to that of Theorem 2.2. □

Theorem 2.5 Let X be an n-Banach space. Then c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ) are Banach spaces under the norm (2.1).

Proof Let Y be any one of the spaces c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ). Let ( x i ) be any Cauchy sequence Y. Let x 0 >0 be fixed and t>0 be such that for a 0<ε<1, ε x 0 t >0 and x 0 t1. Then there exists a positive integer n 0 such that

x i x j ( s ) 0 < ε x 0 t for all i,j n 0 .

Using (2.1), we get

inf { ρ : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k j ) ρ , z 1 , , z n 1 X ) 1 } < ε x 0 t for all i,j n 0 .

Hence we have

sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k j ) x i x j ( s ) 0 , z 1 , , z n 1 X ) 1for all i,j n 0 .

It follows that for every z 1 ,, z n 1 X,

M k ( Δ ( s ) m ( x k i x k j ) x i x j ( s ) 0 , z 1 , , z n 1 X ) 1for each k1 and for all i,j n 0 .

For t>0 with M k ( t x 0 2 )1, for all k1, we have

M k ( Δ ( s ) m ( x k i x k j ) x i x j ( s ) 0 , z 1 , , z n 1 X ) M k ( t x 0 2 ) for every non-zero  z 1 ,, z n 1 X.

This implies that

Δ ( s ) m ( x k i x k j ) , z 1 , , z n 1 X t x 0 2 ε t x 0 = ε 2 for every non-zero  z 1 ,, z n 1 X.

Hence ( Δ ( s ) m x k i ) is a Cauchy sequence in X for all kN. Since X is an n-Banach space, ( Δ ( s ) m x k i ) is convergent in X for all kN. For simplicity, let lim i Δ ( s ) m x k i = y k for each kN. By taking k=1,2,,ms, , we can conclude that

lim i x k i = x k (say) exist for each kN.

Now we can find that

lim j [ inf { ρ : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k j ) ρ , z 1 , , z 2 X ) 1 } ] <εfor all i n 0 .

Then, using the continuity of Orlicz functions, we have

lim j [ inf { ρ : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i lim j x k j ) ρ , z 1 , , z n 1 X ) 1 } ] < ε for all  i n 0 .

Hence we have

inf { ρ : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z 2 X ) 1 } <εfor all i n 0 .

It follows that ( x i x)Y. Since ( x i )Y and Y is a linear space, so we have x= x i ( x i x)Y.

This completes the proof of the theorem. □

The following corollary is due to Lemma 1.2.

Corollary 2.6 If X is a Banach space under the standard n-norm, then c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ) are Banach spaces under the norm

x ( s ) 0 =inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m x k ρ , z 1 , , z n 1 S ) 1 } .

For the following results, let us assume Y to be any one of the spaces c 0 (X,M, Δ ( s ) m ), c(X,M, Δ ( s ) m ) and (X,M, Δ ( s ) m ).

Theorem 2.7 If ( x i ) converges to an x in Y in the norm ( s ) 0 defined by (2.1), then ( x i ) also converges to x in the derived norm ( s ) r defined by (2.3) for r=1.

Proof Let ( x i ) converge to x in Y in the norm ( s ) 0 . Then

x i x ( s ) 0 0as i.

Using (2.1), we get

inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 1 X ) 1 } 0as i.

So, for any linearly independent set { a 1 , a 2 ,, a n }, we have

inf { ρ > 0 : sup k 1 , z 1 , , z n 2 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 2 , a j X ) 1 } 0 as  i  and for each  j = 1 , , n .

Hence by (1.1), we get

inf { ρ > 0 : sup k 1 , z 1 , , z n 2 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 2 ) 1 } 0as i.

Thus

x i x ( s ) 1 0as i.

Hence ( x i ) converges to x in the norm ( s ) 1 . □

If X is equipped with the standard n-norm and the derived norm is with respect to an orthonormal set, then the converse of the above theorem is also true.

Theorem 2.8 Let X be a standard n-normed space and the derived (n1)-norm on X is with respect to an orthonormal set. Then ( x i ) is convergent in Y in the norm ( s ) 0 defined by (2.1) if and only if ( x i ) is convergent in Y in the derived norm ( s ) r defined by (2.3) for r=1.

Proof In view of the above theorem, it is enough to prove that ( x i ) is convergent in the norm ( s ) 1 implies ( x i ) is convergent in the norm ( s ) 0 .

Let ( x i ) converge to x in Y in the norm ( s ) 1 . Then

x i x ( s ) 1 0as i.

Using (2.3) for r=1, we get

inf { ρ > 0 : sup k 1 , z 1 , , z n 2 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 2 ) 1 } 0as i.

Now one may observe that

Δ ( s ) m ( x k i x k ) , z 1 , , z n 1 S Δ ( s ) m ( x k i x k ) , z 1 , , z n 2 S z n 1 S for every non-zero  z 1 , , z n 1 X ,

where , , S and S on the right-hand side denote the standard (n1)-norm and the usual norm on X, respectively. Since the derived (n1)-norm on X is with respect to an orthonormal set, using Lemma 1.3, we have

Δ ( s ) m ( x k i x ) , z 1 , , z n 1 S n Δ ( s ) m ( x k i x ) , z 1 , , z n 2 z n 1 S

and in this case , , on the right-hand side is the derived (n1)-norm which we used to define the norm ( s ) 1 .

Hence

inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 1 S ) 1 } inf { ρ > 0 : sup k 1 , z 1 , , z n 2 X M k ( n Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 2 z n 1 S ) 1 } .

It follows that

inf { ρ > 0 : sup k 1 , z 1 , , z n 1 X M k ( Δ ( s ) m ( x k i x k ) ρ , z 1 , , z n 1 S ) 1 } 0as i.

Hence x i x ( s ) 0 0 as i.

That is, ( x i ) converges to x in Y in the norm ( s ) 0 . □

Using Lemma 1.3, we get the following corollary.

Corollary 2.9 Let X be a standard n-normed space and let the derived (nr)-norms on X be with respect to an orthonormal set. Then a sequence in Y is convergent in the norm ( s ) 0 defined by (2.1) if and only if it is convergent in the derived norm ( s ) 1 and, by induction, in the derived norm ( s ) r defined by (2.3) for all r=1,,n1. In particular, a sequence in Y is convergent in the norm ( s ) 0 if and only if it is convergent in the derived norm ( s ) n 1 , defined by

x ( s ) n 1 =inf { ρ > 0 : sup k M k ( Δ ( s ) m x k ρ ) 1 } .
(2.4)

Theorem 2.10 Let X be a standard n-normed space and let the derived (nr)-norms on X for all r=1,,n1 be with respect to an orthonormal set. Then Y is complete with respect to the norm ( s ) 0 defined by (2.1) if and only if it is complete with respect to the derived norm ( s ) 1 defined by (2.3). By induction, Y is complete with respect to the norm ( s ) 0 if and only if it is complete with respect to the derived norm ( s ) n 1 defined by (2.4).

Proof By replacing the phrases ‘( x i ) converges to x’ with ‘( x i ) is Cauchy’ and ‘ x i x’ with ‘ x i x j ’, we see that the analogues of Theorem 2.7, Theorem 2.8 and Corollary 2.9 hold for Cauchy sequences. This completes the proof. □

Remark Analogues of Theorem 2.4, Theorem 2.5, Corollary 2.6, Theorem 2.7, Theorem 2.8, Corollary 2.9 and Theorem 2.10 hold for the spaces c 0 (X,M, Δ s m ), c(X,M, Δ s m ) and (X,M, Δ s m ).

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Acknowledgements

The author is grateful to three anonymous referees for careful reading of the paper and for helpful comments that improved the presentation of the paper. The author is also grateful to the University Grant Commission, New Delhi-110002, India for sponsoring a MRP under F. No. 39-935/2010 (SR) in the area of this research paper.

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Dutta, H. An Orlicz extension of difference sequences on real linear n-normed spaces. J Inequal Appl 2013, 232 (2013). https://doi.org/10.1186/1029-242X-2013-232

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Keywords

  • n-norm
  • Orlicz function
  • difference operator
  • completeness
  • convex space
  • topological equivalence