The main purpose of this paper is to introduce invariant convergence in intuitionistic fuzzy normed space. Following which we present some characteristics of this notion with respect to intuitionistic fuzzy norm. We also define strongly invariant convergence, ideal invariant convergence and invariant ideal convergence in intuitionistic fuzzy normed space. After that, we establish the relationship between these notions with respect to intuitionistic fuzzy norm. Lastly, we define ideal invariant Cauchy and invariant ideal Cauchy criteria for sequences in intuitionistic fuzzy normed space and relate it to their convergence notion.
Fast [25] and Schoenberg [25], individually generalized usual convergence and introduced statistical convergence for real sequences. Basically, statistical convergence is defined by using the concept of natural density of subsets of . Following which, Kostyrko et al. [8] further extended statistical convergence and defined ideal convergence (in short I-convergence). Basically, the concept of ideal I of is used in the definition of I-convergence. An ideal I is a subset of powerset P (X) of any set X such that ∅ ∈ I, E ∪ F ∈ I ∀ E, F ∈ I and F ∈ I whenever E ∈ I and F ⊂ E . An ideal I is said to be non-trivial ideal if it is not equal to the power set and ideal I is said to be an admissible ideal if {{x} : x ∈ X} ⊂ I . A filter was defined as the sets for which and whenever Kostyrko et al. [8] proposed that one can find a filter associated to an ideal and can be defined as where is a non trivial ideal. Savas and Das [22] gave a new generalized statistical convergence and named it the ideal statistical convergence. In this article, we denote ideal statistical convergence by I
δ-convergence.
In 1948, Lorentz [10] defined a new type of generalized convergence and called it the almost convergence. Following which, almost convergence was slightly generalized by Raimi [19]. This notion is known as σ-convergence. Mursaleen [11, 13] estalished some new invariant matrix summability methods. Nuray and Savas [16] introduced invariant statistical convergence and A-invariant statistical convergence. Later on, Mursaleen and Edely [12] used σ-uniform density for subsets of natural numbers and discussed the notion of statistical convergence via invariant means. Nuray et al. [15] introduced I
σ-convergent sequence and proved some inclusion based results between invariant convergence and I
σ-convergence. For more information, one can refer to [3, 24].
The maiden theory of fuzzy logic is initiated by Zadeh [26] in 1965. He defined the concept of fuzzy sets which is basically the extension of crisp sets. Atanassov [1] further generalized fuzzy sets and introduced intuitionistic fuzzy sets in 1986. Following which, Park [18] defined intuitionistic fuzzy metric space and also established some properties-based results. After that, Saadati and Park [21] put forward the idea of intuitionistic fuzzy euclidian normed spaces and Cooker [14] and Saadati [20], individually further introduced intuitionistic fuzzy topological space. Karakus et al. [7] introduced the statistically convergent sequence in intuitionistic fuzzy normed spaces(IFNS). On the other hand, Kumar and Kumar [9] presented ideal convergence for sequences in IFNS. Later on, this notion was further defined for double sequences in fore-said space by Mursaleen et al. [14]. Savas and Gürdal [23] discussed some methods of summability in IFNS and establised relations between them. Recently, Huban [6] defined Lacunary ideal invariant convergence (in Wijsman sense) for set sequence in intuitionistic fuzzy metric space.
In this article, we discuss the notion of invariant convergence, invariant ideal convergence and ideal invariant convergence for sequences in the settings of intuitionistic fuzzy normed space. We also study the behaviour and relationships of these notion in IFNS.
First, we recall some concepts related to these notions which are useful to understand this paper.
Definition 1.1. [20] The five-tuple (X, τ1, τ2, ∗ , ◊) is said to be an intuitionistic fuzzy normed space (in short IFNS) if X is a vector space over a field , ∗ is a continuous t-norm, ◊ is a continuous t-co-norm and τ1 & τ2 are the fuzzy sets on X × (0, ∞) satisfy the following conditions ∀ y, z ∈ X and s, t > 0 :
(a) τ1 (y, s) + τ2 (y, s) ≤1,
(b) τ1 (y, s) >0,
(c) τ1 (y, s) =1 iff y = 0,
(d) , ∀a ≠ 0,
(e) τ1 (y, t) * τ1 (z, s) ≤ τ1 (y + z, t + s),
(f) τ1 (y, .) : (0, ∞) → [0, 1] is continuous,
(g) τ1 (y, s) =1 and τ1 (y, s) =0,
(i) τ2 (y, s) >0,
(j) τ2 (y, s) =0 iff y = 0,
(l) , ∀a ≠ 0,
(m) τ2 (y, t) ◊ τ2 (z, s) ≥ τ2 (y + z, t + s),
(n) τ2 (y,) : (0, ∞) → [0, 1] is continuous,
(o) τ2 (y, s) =0 and τ2 (y, s) =1
Then, (τ1, τ2) is called intuitionistc fuzzy norm (in short IFN).
Example 1.1. If (X, || . ||) forms a normed linear space, let for all a, b ∈ [0, 1] , t-norm is defined as a * b = ab and t-co-norm is defined as a ◊ b = min {a + b, 1}, then for any y ∈ X and ∀s > 0, consider
Then (X, τ1, τ2, ∗ , ◊) forms an intuitionistic fuzzy normed space.
Lemma 1.1. [20] If 0 < sk < 1, 1 ≤ k ≤ 7. ∗ and ◊ are continuous t-norm and continuous t-conorm, respectively. Then
Definition 1.2. Let (X, τ1, τ2, ∗ , ◊) be an IFNS, then a sequence {yn} in X is said to be convergent to ξ ∈ X if for any ε ∈ (0, 1) and s > 0, there exists such that
We denote it by {yn} ⟶ ξ with respect to IFN (τ1, τ2).
We denote 1 - τ1 (y, s) by . So in Definition 1.2, τ1 (yn - ξ, s) >1 - ε will be replace by . We use this notation in some proofs of this paper only for simplicity.
Definition 1.3. Let I be a non-trivial admissible ideal of and ω be the space of all real sequences. The ideal convergence of a sequence {yn} ∈ ω to a number implicates that ∀ ε > 0, the set
Definition 1.4. Let P is a subset of and Pj = {k ≤ j : k ∈ P}. Then the natural density δ (P) is
provoided that limit exists. The vertical lines denotes cardinality of set.
Definition 1.5. Let I
δ be ideal of those subset of such that natural density of set is zero. A sequence {yn} is said to be I
δ- convergent to ξ if for any ε > 0 such that
That is δ (A
ε) =0. We denote it by . Obviously it is a particular case of ideal convergence.
Definition 1.6. Let σ is a map of into itself. Then a continuous linear functional φ defined on space of all bounded sequences ℓ∞ is said to be an invariant mean if φ (y) ≥0 for all y ∈ ℓ ∞, φ is normal and φ (yn) = φ (y
σ(n)).
Definition 1.7. A sequence {yn} is said to be invariant convergent(or σ- convergent) to ξ if its all invariant means coincide with ξ. A bounded sequence {yn} is said to be invariant convergent(or σ- convergent) to ξ if uniformly in k. Here . In this case, we denote it as .
Definition 1.8. Let A = {σ (k) ≤ j ≤ σj (k) : n ∈ P} for and K (σ (k) , σj (k)) is the cardinality of set A. Suppose and then lower (and upper ) σ-density of set P is defined as
provoided that limit exists. Note that ρ
σ (P) is said to be σ-density of set P if Obviously for any , and it reduced to uniform density [2] if σ (k) = k + 1.
Example 1.2. If set P is the union of all set {10n + 1, 10n + 2, . . . , 10n + n} for all natural number n = 1 to ∞. Then natural density δ (P) of set P is zero. On the other hand, lower σ-density of set P is zero but upper σ-density of set P is one.
Results
Throughout the paper, I is a non-trivial admissible ideal defined on and IFNS means intuitionistic fuzzy normed space. This section is divided in two subsection. In first subsection, we define invariant convergence along with invariant Cauchy criterion in IFNS and prove some properties of these notions. In second subsection, we define strongly σ-convergence, σ-ideal convergence and ideal σ-convergence in IFNS. We also establish some connection bewteen them. At last, we define σ-ideal Cauchy and ideal σ-Cauchy sequence in IFNS.
Invariant convergence in IFNS
Definition 2.1. Let (X, τ1, τ2, ∗ , ◊) is an IFNS and
for any sequence {yn} in X. Then invariant convergence of sequence {yn} to ξ in IFNS is define as if for all s > 0
uniformly in k. That is for any preassigned ε ∈ (0, 1) and s > 0, there exists a such that ∀j > j0 and
In this case, we write with respect to IFN (τ1, τ2).
Remark 2.1. In IFNS, it is obvious that usual convergence implies σ-convergence and every σ-convergent sequence is bounded sequence with respect to IFN.
Theorem 2.1.If a sequence {yn} in IFNS is such that with respect to IFN (τ1, τ2), then limit will be unique.
Proof. Let on contrary that sequence {yn} in IFNS is such that as well as with ξ1 ≠ ξ2 . Then we have for any preassigned ε ∈ (0, 1), there exists r ∈ (0, 1) such that (1 - r) ∗ (1 - r) ≥ (1 - ε) and r ◊ r ≤ ε. For any s > 0, there exists and such that
as well as
Now for any and take any , we have
and
Which implies that ξ1 = ξ2. Hence we reached at a contradiction.□
Theorem 2.2.If sequence {yn} and {zn} in IFNS is such that and with respect to IFN (τ1, τ2), then
(1) with respect to IFN (τ1, τ2).
(2) with respect to IFN (τ1, τ2), here a is scalar.
Proof. (1) Let sequence {yn} and {zn} in IFNS is such that and with respect to IFN (τ1, τ2) and
and
respectively. Then we have for any preassigned ε ∈ (0, 1), there exists r ∈ (0, 1) such that (1 - r) ∗ (1 - r) ≥ (1 - ε) and r ◊ r ≤ ε. For any s > 0, there exists and such that
and
Now for any and take any , we have
and
Hence with respect to IFN (τ1, τ2).
(2) If a = 0, then proof is obvious. If a ≠ 0 and with respect to IFN (τ1, τ2) then for any preassigned ε ∈ (0, 1) and s > 0, such that for all j > j0 and for all
Now for any j > j0 and for any , we have
and
Hence with respect to IFN (τ1, τ2).□
Definition 2.2. Let (X, τ1, τ2, ∗ , ◊) is an IFNS and
for any sequence {yn} in X. Then invariant Cauchy criterion of sequence {yn} in IFNS is define as if for any preassigned ε ∈ (0, 1) and s > 0, there exists a such that ∀j, j′ > j0 and
Theorem 2.3.A sequence in IFNS is invariant convergent if and only if sequence is invariant Cauchy with respect to IFN (τ1, τ2).
Proof. Let sequence {yn} is invariant convergent to ξ in an IFNS and
Then for any preassigned ε ∈ (0, 1), there exists r ∈ (0, 1) such that (1 - r) ∗ (1 - r) ≥ (1 - ε) and r ◊ r ≤ ε. For any s > 0, there exists such that
It is obvious that ∀j, j′ > j0 and we have
and
Hence sequence {yn} is invariant Cauchy with respect to IFN (τ1, τ2).
Conversely, let sequence {yn} is invariant Cauchy with respect to IFN (τ1, τ2). Then for any preassigned ε ∈ (0, 1) there exists r ∈ (0, 1) such that (1 - r) ∗ (1 - r) ≥ (1 - ε) and r ◊ r ≤ ε. For any s > 0, there exists a such that ∀j, j′ > j0 and
Fixing k = k0, hence (2.1) cauchy implies considering k = k′ = k0 that satisfies Cauchy criterion so it converges to some ξ. For any s > 0, there exists such that
Now for any and take any j > j′ = max {j0, j1}, we have
and
Hence with respect to IFN (τ1, τ2).□
Strongly σ-convergence, σ-ideal convergence and ideal σ-convergence in IFNS
Definition 2.3. Let (X, τ1, τ2, ∗ , ◊) is an IFNS and I
σ is ideal of those subsets of whose σ-density is zero. Then invariant ideal convergence(or σ-ideal convergence) of a sequence {yn} to ξ in IFNS is define as if for any preassigned ε ∈ (0, 1) and s > 0 the following set
means σ-density of set A
ε is zero. That is for all ε ∈ (0, 1) and s > 0
In this case, we write with respect to IFN (τ1, τ2).
Definition 2.4. Let (X, τ1, τ2, ∗ , ◊) is an IFNS, I is a non-trivial admissible ideal of and
for any sequence {yn} in X. Then ideal invariant convergence(or ideal σ-convergence) of a sequence {yn} to ξ in IFNS is define as if for any preassigned ε ∈ (0, 1), s > 0 and for all
In this case, we write with respect to IFN (τ1, τ2).
Remark 2.2. In IFNS,
1) clearly, invariant I-convergence implies I-convergence implies I-invariant convergence but converse need not to be true.
2) if a sequence {yn} is invariant convergent to ξ then obviously sequence will be ideal invariant convergent to ξ but not invariant ideal convergent in general.
Example 2.1. In Example 1.1, suppose X is set of real numbers with usual norm and I = I
δ. Let sequence {yn} is such that
Clearly, sequence {yn} is invariant I
δ-convergent so it is I
δ-convergent and I
δ-invariant convergent but unfortunately sequence is not convergent.
Example 2.2. In Example 1.1, suppose X is set of real numbers with usual norm and I = I
δ. Let σ (k) = k + 1 and sequence {yn} is such that
Here P is a set as defined in Example 1.2. Clearly, sequence {yn} is I
δ-convergent but not invariant I
δ-convergent.
Example 2.3. In Example 1.1, suppose X is set of real numbers with usual norm and I = I
δ. Let σ (k) = k + 1 and sequence {yn} is such that
Clearly, sequence {yn} is invariant convergent to 1/2 as well as I
δ-invariant convergent to 1/2 but unfortunately sequence is neither I
δ-convergent nor invariant I
δ-convergent.
Parallel results as Theorem 2.1, 2.2 can be easily establised for σ-ideal convergence and ideal σ-convergence with respect to IFN (τ1, τ2).
Theorem 2.4.Let be the space of all bounded and invariant ideal convergent sequences with respect to IFN (τ1, τ2), then and is a closed linear subset of , here denotes the space of all bounded sequences with respect to IFN (τ1, τ2).
Proof. Let sequence is convergent to y such that . Now we show that . Let sequence ym is invariant ideal convergent to ξm with respact to IFN (τ1, τ2), for each and take sequence {εm} with , for preassigned ε > 0. Clearly, we can choose a natural number m such that . For any given δ ∈ (0, 1), there exists a natural number j0 such that for all j ≥ j0
and
Therefore, ∃ a natural number n such that σ (k) ≤ n ≤ σj (k) for which and . Hence
Hence sequence satisfies Cauchy criterion with respect to IFN (τ1, τ2). Therefore, ∃ a ξ such that {ξm} converges to ξ. Now we show that y invariant ideal convergent to ξ with respect to (τ1, τ2). For any preassigned ε ∈ (0, 1) and s > 0, take such that ,
or . Hence we have
Therefore,
Hence y = {yn} is invariant ideal convergent to ξ with respect to (τ1, τ2).□
A similar result as Theorem 2.4 can be proved for ideal invariant convergence.
Proposition 2.5.Let (X, τ1, τ2, ∗ , ◊) is an IFNS. Let {yn} be a sequence in X. For every ε > 0 and s > 0, these following are equivalent:
(a) with respect to IFN (τ1, τ2);
(b) and ;
(c) and ;
(d) and ;
(e) and I
σ - lim τ2 (yn - ξ, s) =0 .
Proposition 2.6.Let (X, τ1, τ2, ∗ , ◊) is an IFNS, I be a non-trivial admissible ideal of and
for any sequence {yn} in X. For every ε > 0, s > 0 and for all , these following are equivalent:
(a) with respect to IFN (τ1, τ2);
(b) and ;
(c) and ;
(d) and ;
(e) and I - lim τ2 (hjk - ξ, s) =0 .
Theorem 2.7.Let (X, τ1, τ2, ∗ , ◊) is an IFNS, then every bounded invariant ideal convergent sequence in X is ideal invariant convergent with respect to IFN (τ1, τ2).
Proof. Let sequence {yn} is bounded and invariant ideal convergent to ξ in X and
Suppose for any ε ∈ (0, 1), . Then
and
Hence sequence {yn} is invariant convergent to ξ and hence it is ideal invariant convergent.□
Example 2.4. Take IFNS with τ1 and τ2 as Example 1.1 with usual norm and I = I
δ. Let σ (k) = k + 1 and sequence {yn} is such that
Clearly, sequence {yn} is invariant convergent to zero so I
δ-invariant convergent to zero but unfortunately sequence is not invariant I
δ-convergent.
Definition 2.5. Let (X, τ1, τ2, ∗ , ◊) is an IFNS, then strongly invariant convergence(or strongly σ-convergence) of sequence {yn} to ξ in IFNS is define as if for all s > 0
uniformly in k. In this case, we write with respect to IFN (τ1, τ2).
Theorem 2.8.Let {yn} be a sequence in IFNS such that {yn} is strongly σ-convergent sequence then {yn} is σ-ideal convergent with respect to IFN.
Proof. Let (X, τ1, τ2, ∗ , ◊) is an IFNS and {yn} is a sequence in X such that {yn} is strongly σ-convergent to ξ with respect to IFN (τ1, τ2). Then for any preassigned ε ∈ (0, 1) and s > 0, there exists a such that ∀j > j0 and
From the following inequalities
and
we have for any δ > 0
and
So we have A ∪ B ⊂ {1, 2, . . . , j0}. Therefore
Hence with respect to IFN (τ1, τ2).□
Theorem 2.9.Let {yn} be a sequence in IFNS such that {yn} is bounded and σ-ideal convergent sequence then {yn} is strongly σ-convergent with respect to IFN.
Proof. Let (X, τ1, τ2, ∗ , ◊) is an IFNS and {yn} is a sequence in X such that {yn} is bounded and σ-ideal convergent to ξ with respect to IFN (τ1, τ2). Then for any preassigned ε, δ ∈ (0, 1), s > 0 and for all
and ∃s > 0 and M ∈ (0, 1) such that
Now since for each
and
Hence from (2.6), we can conclude that sequence {yn} is strongly σ-convergent to ξ in X.□
Definition 2.6. Let (X, τ1, τ2, ∗ , ◊) is an IFNS and I
σ is ideal of those subsets of whose σ-density is zero. Then invariant ideal Cauchy criterion(or σ-ideal Cauchy criterion) for a sequence {yn} in IFNS is define as if for any preassigned ε ∈ (0, 1) and s > 0, such that the following set
means σ-density of set B
ε is zero.
Definition 2.7. Let (X, τ1, τ2, ∗ , ◊) is an IFNS, I is a non-trivial admissible ideal of and
for any sequence {yn} in X. Then ideal invariant Cauchy criterion(or ideal σ-Cauchy criterion) for a sequence {yn} in IFNS is define as if for any preassigned ε ∈ (0, 1), s > 0, such that the following set for all
Theorem 2.10.Let (X, τ1, τ2, ∗ , ◊) is an IFNS. If a sequence in X is invariant ideal convergent then sequence satisfies invariant ideal Cauchy criterion in X.
Theorem 2.11.Let (X, τ1, τ2, ∗ , ◊) is an IFNS. A sequence in X is ideal invariant convergent if and only if sequence satisfies ideal invariant Cauchy criterion in X.
Applicaton. For the very first time, Zadeh [26] initiated the fuzzy theory and presented the concept of fuzzy sets in the year 1965. A progressive development has been made for the advancement of fuzzy theory. While seeing the complexity of nowadays real-world problems, it was important to discover the fuzzy analogues for the theory of classical sets. There are numerous numbers of applications of fuzzy theory in the various fields of engineering and science (in particular, in fuzzy physics, nonlinear dynamical systems, computer programming, chaos control, population dynamics, etc.) so it made a huge positive impact on the interest of researchers towards the fuzzy theory. In quantum mechanics, the position space representation is incapable to deal with such situations where the determined or given space-time points are fuzzy numbers, hence the sequence of these points forms a fuzzy numbers sequence. Therefore, fuzzy norm/intuitionistic fuzzy norm is the desired structure to tackle these conditions beacuse it is generalized and unified structure. When used space does not fulfill our motive then intuitionistic fuzzy norm plays a pivotal role as we can use the inexactness of the norm to deal with such situations. Invariant ideal convergence and ideal statistical convergence are non-matrix methods of summability and are incompatible. In various fields of engineering and science, we often come across the double sequences, i.e. sequences of matrices and certainly there are situations where the idea of ordinary convergence does not work therefore a generalized convergence is needed to deal this situation, namely the ideal convergence. Some basic algebraic results on invariant ideal convergence hold for both sequence and double sequence due to analogous results for sequences; although the proofs are rather trivial in both cases. Despite that, there are some concepts defined for double sequences such that these concepts are preserved by this correspondence. In particular, this holds for the concepts of invariant ideal Cauchy double sequences in IFNS such that they can yield a desirable framework and superior tool.
Conclusion
We define of invariant convergent, invariant ideal convergent, ideal invariant convergent and invariant Cauchy, invariant ideal Cauchy, ideal invariant Cauchy sequence in intuitionistic fuzzy normed space. We discuss some properties of invariant convergent sequence in intuitionistic fuzzy normed space. We futher establish the connection among numerous sequences in intuitionistic fuzzy normed space. Since invariant convergence via ideal is more unified and generalized convergence of many well-known convergence and intuitionistic fuzzy normed space is also an extension of various famous spaces, so our establised results are in more genral settings and these new results will further help the researchers to expand their work in the area of functional analysis in view of fuzzy theory.
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