1. Introduction
The concept of a fuzzy norm on a vector space was first introduced by Katsaras [
1]. After his works, Felbin [
2] introduced an alternative definition of a fuzzy norm (namely, the Felbin fuzzy norm) related to a fuzzy metric of Kaleva–Seikkala’s type [
3]. Another fuzzy norm (namely, the B-S fuzzy norm) was defined by Bag and Samanta [
4]. Bag and Samanta also conducted a comparative study of the relationship between their fuzzy norms and the fuzzy norms defined by Felbin [
5]. Recently, topological properties including an inner product, fuzzy sets, and a boundedness have been studied according to Felbin type fuzzy norms and B-S type fuzzy norms [
6,
7,
8]. Cho et al. systemically provided classical and recent results of fuzzy normed spaces and fuzzy operators in their book [
9].
The approximation property (AP) is a key notion for the research of functional analysis. The AP indicates that the identity operator on an Banach space can be approximated in the compact open topology by finite rank operators [
10,
11,
12,
13]. The AP has been applied to study Shauder basis and operator theory. In 2010, Yilmaz introduced the approximation property in B-S fuzzy normed spaces [
14]. The second author [
15] modified Yilmaz’s definitions and introduced the approximation property and the bounded approximation property in B-S fuzzy normed spaces. Related works have emerged from fuzzy theory. We would refer to intuitionistic fuzzy Banach space theory [
16].
In this paper we establish approximation properties in Felbin fuzzy normed spaces. Moreover, we will conduct a comparative study among approximation properties in B-S fuzzy normed spaces and Felbin fuzzy normed spaces. We characterize approximation properties in Felbin fuzzy normed spaces. The advantage of our context is to make tools for operators in fuzzy analysis since we develop the representation of finite rank operators.
Our paper is organized as follows.
Section 2 comprises some preliminary results. In
Section 3, we define approximation properties and bounded approximation properties in Felbin fuzzy normed spaces. Furthermore, we provide several examples related to these properties. In
Section 4, we give relations by making a comparative study of the approximation properties in fuzzy normed spaces defined by Bag and Samanta and Felbin.
Section 5 is devoted to developing the representation of a finite rank operator as tools for analyzing approximation properties. In
Section 6, we apply this representation to establish characterizations of approximation properties in Felbin fuzzy normed spaces.
2. Preliminaries
Definition 1. (See [5].) A mapping is called a fuzzy real number with α-level set , if it satisfies the following conditions: (i) there exists a such that
(ii) for each , there exist real numbers such that the α-level set is equal to the closed interval .
The set of all fuzzy real numbers is denoted by
. If
and
whenever
, then
is called a non-negative fuzzy real number and
denotes the set of all non-negative fuzzy real numbers. Since each
can be considered as the fuzzy real number
denoted by
hence it follows that
can be embedded in
(See [
5]).
Definition 2. (See [5].) Let X be a vector space over . Assume the mappings are symmetric and non-decreasing in both arguments, and that and . Let . The quadruple is called a Felbin fuzzy normed space with the fuzzy norm , if the following conditions are satisfied: (F1) if , then
(F2) if and only if ,
(F3) for and ,
(F4) for all ,
(F4L) whenever and
(F4R) whenever and
We assume that
(F5) for any sequence in such that such that for all . In this paper we fix and for all and we write .
Definition 3. (See [5].) Let be a Felbin fuzzy normed space. A sequence of X is said to converge to () if for all . A subset A of X is called compact in if each sequence of elements of A has a convergent subsequence in . Definition 4. (See [17].) Let and be Felbin fuzzy normed spaces. The linear operator is said to be strongly fuzzy bounded if there is a real number such that for all . We will denote the set of all strongly fuzzy bounded operators from to by . Then is a vector space. For all we denote bywhere M is a positive real number. is called bounded in
if
for some
. Moreover, we denote the set of all finite rank strongly fuzzy bounded operators from
to
by
. Then
is a subspace of
. We similarly define
for some
. Now, we provide definitions of the approximation properties in Felbin fuzzy normed spaces. For the definition and properties of the
-level set (
), see [
3,
18].
Definitions of a B-S fuzzy norm and a B-S fuzzy antinorm are well mentioned in [
3]. Thus, we only give additional properties related to them.
Definition 5. (See [17].) Let be a B-S fuzzy normed space and be a B-S fuzzy antinormed space. We assume that
(N6) for all implies that .
(N7) For is continuous on and strictly increasing on
Moreover, we assume that
(6) for all implies that .
(7) For is continuous on and strictly decreasing on
Also, we need the new definition of compactness in given a B-S fuzzy norm and a B-S fuzzy antinorm as follows.
Definition 6. Let N be a B-S fuzzy norm and be a B-S fuzzy antinorm on a vector space X (briefly, ). A subset A of X is called compact in if each sequence of elements of A has a convergent subsequence in where A sequence of X is said to converge to () if for each , Definition 7. (a) Let and be B-S-fuzzy normed spaces. The linear operator is said to be a strongly fuzzy bounded if there exists a positive real number M such that for all and .
(b) Let and be given. The linear operator is said to be a strongly fuzzy bounded if there exists a positive real number M such that and for all and .
Lemma 1. (See [5]) Let be a Felbin fuzzy normed space and , . Let N and be two functions in defined byandThen N is a B-S fuzzy norm satisfying (N6) and is a B-S fuzzy antinorm satisfying , (i) N satisfies (N6),
(ii) satisfies ,
(iii) for each ,
(iv) for each ,
(v) , where .
Lemma 2. (See [5]) Let N be a B-S fuzzy norm and be a B-S fuzzy antinorm on a linear vector space X satisfying the conditions (i)–(v) of Lemma 1. DefineandThen there is a Felbin fuzzy norm on X such that , and . Lemma 3. (See [5]) Let be a Felbin fuzzy normed space such that satisfies the condition (F5), N and be two functions on defined in Lemma 1 and be the fuzzy norm defined in Lemma 2. Then we have . Note that, if
, the linear space of all real numbers, we define a function
by
Then is a fuzzy norm on and -level sets of are given by for all .
Definition 8. (See [19].) A strongly fuzzy bounded linear operator defined from a Felbin fuzzy normed space to ( is called a strongly fuzzy bounded linear functional. Denote by the set of all strongly fuzzy bounded linear functionals over . Definefor all . Remark 1. Definition 4.1 came from Bag and Samanta [18]. Although they defined a strongly fuzzy bounded linear operator differently from this paper, the two definitions are the same in the case of functionals. The following lemma is the Hahn–Banach theorem on fuzzy normed spaces ([
19], Theorem 7.1).
Lemma 4. Let be a Felbin fuzzy normed space and Z be a subspace of X. Let f be a strongly fuzzy bounded linear functional defined on . Then there exists a strongly fuzzy bounded linear functional on X such that and .
Now we provide the definitions of approximation property in B-S fuzzy normed spaces [
15].
Definition 9. Let be a B-S fuzzy normed space. A fuzzy normed space is said to have the approximation property, if for every compact set K in and for each and , there exists a strongly fuzzy bounded such that 3. Approximation Properties
In this section, we introduce definitions of approximation properties in Felbin fuzzy normed spaces and several examples.
Definition 10. A Felbin fuzzy normed space is said to have the approximation property (AP), if for every compact set K in and for each and , there exists an operator such thatfor every . Definition 11. Let λ be a positive real number. A Felbin fuzzy normed space is said to have the λ-bounded approximation property (λ-BAP), if for every compact set K in and for each and , there exists an operator such thatfor every . Also we say that has the BAP if has the λ-BAP for some . By definition, we can have the following proposition.
Proposition 1. The following are equivalent for a Felbin fuzzy normed space .
(a) has the AP.
(b) If is a Felbin fuzzy normed space, then for every , every compact set K in and for each and , there exists an operator such thatfor every . (c) If is a Felbin fuzzy normed space, then for every , every compact set K in and for each and , there exists an operator such thatfor every . Proposition 2. Let be a Felbin fuzzy normed space and . Suppose that there exists a sequence such that for every . Then has the AP.
Given a Felbin fuzzy normed space
, we recall
By the proof of ([
15], Lemma 4.2), we have the following.
Lemma 5. Let be a Felbin fuzzy normed space and K be a compact subset in . Then there exists a finite set in K such that for , we have for some .
Proof of Proposition 2. Let
be a sequence in
such that
for ever
. Let
K be a compact in
and
and
. By Lemma 5, there exists a finite set
such that for
, we have
for some
. Then there exists
such that if
, then
for each
i. Let
and take
i such that
. Then for
, we have,
Hence
has the AP. □
By Proposition 2, we have the following.
Corollary 1. Let be given. Suppose a Felbin fuzzy normed space has a basis and every natural projection is in . Then has the AP.
The converse of the above corollary may not be true.
Example 1. There exists a Felbin fuzzy normed space which has the AP (even MAP) but does not have a basis.
Proof. Let us consider Banach space
with
. Moreover,
is another norm on
. Now let us define
Then it can be easily shown that
is a fuzzy normed space. Also, we have,
Then it follows that
Then
cannot have a basis because the Banach space
, for
, is not separable. By the argument of ([
14], Example 1),
has the AP. □
Example 2. There exists a Felbin fuzzy normed space which does not have the AP.
Proof. Let us say that a Banach space
does not have the approximation property [
11]. Let us define
It is clear that
for all
. Then
does not have the AP. □
Example 3. There exists a Felbin fuzzy normed space which has the AP but fails the BAP.
Proof. ([
15], Example 4.9) indicates that the Banach space
has the AP but does not have the BAP, where for each
n,
has the AP but does not have the BAP, and its norm is notated by
. Let us define
and
for all
. Now let us define
Then it can be easily shown that
is a fuzzy normed space. Also, we have,
Hence we obtain that
Now we suppose that
has the BAP. Let
K be a compact subset in
. Then it is clear that
K is a compact in
. Let us take
and
. Then, by the assumption, there exist
and
such that
for every
. Then we have
for all
and
hence it is a contradiction.
To show that
has the AP, let
K be a compact subset in
and
. By using the argument of ([
15], Example 4.9), there exists a natural number
and a finite rank operator
such that
for every
where
defined by
and
is the projection given by
Put
. So we have
for every
. Finally, we shall show that
T is a strongly fuzzy bounded. Since
and
are equivalent, there exists
such that
Now we put
. Then, for every
, we obtain
Also, for every
, we obtain
For
, by (2), we have
□
4. Relations Between APs in Fellbin Fuzzy Normed Spaces and APs in B-S Fuzzy Normed Spaces
In this section, we establish relationships between approximation properties in Felbin fuzzy normed spaces and approximation properties in B-S fuzzy normed spaces.
Proposition 3. Let X be a linear space. If X has the AP (BAP) with respect to any Felbin fuzzy norm, then it has the AP (BAP) with respect to any B-S fuzzy norm satisfying condition (N6) and (N7).
Proof. Let
N be a B-S fuzzy norm on
X satisfying (N6) and (N7). Put
. Clearly,
is a fuzzy antinorm on
X satisfying
and
. For
, we define
Then, by ([
5], Theorem 3.2), for each
,
is a norm on
X. Now we define
It is clear that
is a B-S-fuzzy norm satisfying (N6). Moreover it can be easily shown that
and
satisfy (i)–(v) of Lemma 1. Let
for every
. Indeed, we have
for every
. Then, by Lemma 2, there is a Felbin fuzzy norm
on
X such that
,
and
. By ([
17], Theorem 15), we have
Take a compact subset
K of
. Then we claim that
K is a compact subset of
. Indeed, take any sequence
in
K. Then there exist a subsequence
and
x in
K such that
in
. Then
as
,
. i.e.
as
,
. So we have
as
,
. Then
is a convergent sequence in
, hence
K is a compact subset of
. Let
and
. By definition of the AP in B-S fuzzy normed spaces, we shall show that there exists a strongly fuzzy bounded
such that
for every
. By the assumption, there exists an operator
such that
for every
. By definition of
, there exists
such that
Since
is non-increasing, we have
so we have
. Finally, we shall show that
T is sf -bounded operator on
. By definition, we show that there exists a positive real number
M such that
for all
and
. Indeed, since
, there exists a
such that
and
for all
. Then, for all
, we have
so we have
, hence
T is sf-bounded. □
We do not know whether the converse of Proposition 3 is true. However, we obtain the following.
Theorem 1. Let be a Felbin fuzzy normed space such that satisfies the condition (F5). Let N and be two functions in defined in Lemma 1. Then has the AP, if and only if, for every a compact K in and and , there exists a strongly fuzzy bounded such thatfor every . Proof. Sufficiency. Put
for
. Let
N and
be two functions in
defined in Lemma 1. By Lemma 3, we have
and
Take any a compact
K in
. By ([
17], Theorem 24),
K is a compact in
. Let
and
. By the assumption, there exists an operator
such that
for every
. By the argument of Proposition 3, we have
for every
. Also, we can observe that
for all
and
. Indeed, fix
. If
, then we have
If
, then we have
hence we have
for all
. Then we have
. By definition of
, there exists
such that
Since
N is non-decreasing, we have
so we have
. Finally, by ([
17], Theorem 17),
T is strongly fuzzy bounded in
.
Necessity. Let us take any compact
K in
. By ([
17], Theorem 24),
K is a compact in
. Let
and
. By the assumption, there exists a strongly fuzzy bounded
such that
for every
. Then there exists
such that
. Then we have
. Finally, by ([
17], Theorem 18),
T is strongly fuzzy bounded in
. □
The following example shows a partial relationship between the AP in Felbin fuzzy normed spaces and the AP in B-S fuzzy normed spaces.
Example 4. There exists a linear space X such that a Felbin fuzzy normed space does not have the AP and a B-S fuzzy normed space also does not have the AP.
Proof. We use Example 4. Let us define
Clearly, we obtain that
has the condition (N6) and
for each
. Then, it is obvious that
does not have the AP. □
Question. Is there a linear space X such that a Felbin-fuzzy normed space has the AP but a B-S fuzzy normed space does not have the AP for some a felbin fuzzy norm and a B-S fuzzy norm N?
5. The Representation of Finite Rank Strongly Fuzzy Bounded Operators
In this section, we develop the representation of finite rank strongly fuzzy bounded operators.
Theorem 2. Let Y be a subspace of Felbin fuzzy normed space such , Y is closed in . Suppose that . Then there is a strongly fuzzy bounded linear functional f on X such that and .
Proof. Denote
We claim that
. Suppose that
. Take any
. Then there exists
such that
. So, there exists
such that
. Then we have
. Since
Y is a closed subspace of
, hence we have
, it is a contradiction.
Let
for each
and each scalar
. Then
is a linear functional on
such that
and
for each
. For each
and
, we have
so
is a strongly fuzzy bounded linear functional on
and
. Moreover, for each
, we have
for all
, so we have
Since
, we obtain that
, so
. By Lemma 4, we can finish our proof. □
The following corollary gives the representation of finite rank strongly fuzzy bounded operators.
Corollary 2. Let and be Felbin fuzzy normed spaces. If is a finite rank strongly fuzzy bounded linear operator, then there exist and such thatfor all . Proof. Since is a finite dimensional subspace of Y, there exists a basis of . Now fix . Consider Then Z is a finite dimensional subspace of Y and . Since, , Z is closed in , by Theorem 2, there is a strongly fuzzy bounded linear functional on Y such that and . We may assume that . Put . Then is also a strongly fuzzy bounded linear functional on X. Finally, we take any and write where for each n is a scalar depending on x. By properties of , it is clear that for each n. □
6. Characterizations of Approximation Properties in Felbin Fuzzy Normed Spaces
In this section, we establish characterizations of approximation properties in Felbin fuzzy normed spaces. To do this, we develop topological methods in spaces of strongly fuzzy bounded linear operators.
Definition 12. Let and be Felbin fuzzy normed spaces. For a compact , , , and we putLet be the collection of all such s. Then the τ-topology on is the topology generated by . For a net
and
we have
in
if and only if for every compact
and
,
Definition 13. Let and be Felbin-fuzzy normed spaces. For , , , and we putLet be the collection of all such s. Then the -topology on is the topology generated by . For a net
and
we have
in
if and only if for every
and
,
From ([
20], Notation 3.6), we denote by
and
the dual space of
and
respectively.
Definition 14. Let and be Felbin fuzzy normed spaces. Let be the linear span of all linear functionals f on of the form for and where . Then -topology on is the topology generated by .
For a net
and
we have
in
if and only if for every
,
and
Then we provide the following simple proposition. The proof is clear.
Proposition 4. Let and be Felbin fuzzy normed spaces.
(a) τ, and are locally convex topologies.
(b) τ is stronger than and is stronger than .
By the argument of ([
15], Proposition 5.6) and Lemma 5, we have the following.
Proposition 5. Let and be Felbin fuzzy normed spaces. If is a bounded in , then we have on .
To show a relation between and on , we need the following two lemmas. We recall that is the vector space of all -continuous (-continuous) linear functionals on .
Lemma 6. Let and be Felbin fuzzy normed spaces. If , then there exists a finite subset of X and and such that implies .
Proof. By Definition 13, there exists a finite set
of
X and a set
and a set
such that
for all
where
and
for all
. Now we put
and
. We consider a set
. Since
is a descending family of norms on
Y, we obtain
Hence if
, then
. □
By the proof of ([
15], Lemma 5.8) and Lemma 6, we derive the following lemma.
Lemma 7. Let and be Felbin fuzzy normed spaces. Thenand the form of the continuous linear functionals f on is , and for some . Proposition 6. Let and be Felbin fuzzy normed spaces.
(a) If is a convex set in , then .
(b) If is a bounded convex set in , then .
Proof.
(a) By Lemma 6 and ([
21], Corollary 2.2.29), we derive (a).
(b) By Proposition 5 and (a), we prove (b). □
Now, using the results so far, we provide characterizations of a Felbin fuzzy normed space to have the BAP. To prove these characterizations, we need the following lemma. For the proof, we refer to [
22].
Lemma 8. Let be a Felbin fuzzy normed space. Suppose that is a balanced convex subset of . Let . Then the following are equivalent.
(a) T belongs to .
(b) For every such that for all , we have .
Theorem 3. Let be a Felbin fuzzy normed space. Then the following are equivalent.
(a) has λ-BAP.
(b) There exists a net in such that for each , and .
(c) For every , and , if for all , then .
(d) For every , and , iffor all and with , then . Proof. (a)⇔(b)⇔(c) By Lemma 7, Proposition 6, Lemma 8, and the argument of ([
15], Theorem 6.3), it can be deduced,
(c)⇔(d). By Corollary 2, it is clear. □
Remark 2. Theorem 3 (d) implies that the BAP in Felbin fuzzy normed spaces has better characterizations compared with the BAP in B-S fuzzy normed spaces (cf. [15], Theorem 6.3).