Tauberian theorem serves the purpose to recuperate Pringsheim’s convergence of a double sequence from its (C, 1, 1) summability under some additional conditions known as Tauberian conditions. In this article, we intend to introduce some Tauberian theorems for fuzzy number sequences by using the de la Vallée Poussin mean and double difference operator of order r . We prove that a bounded double sequence of fuzzy number which is convergent is summable to the same fuzzy number L . We make an effort to develop some new slowly oscillating and Hardy-type Tauberian conditions in certain senses employing de la Vallée Poussin mean. We establish a connection between the Hardy type and slowly oscillating Tauberian condition. Finally by using these new slowly oscillating and Hardy-type Tauberian conditions, we explore some relations between summable and convergent double fuzzy number sequences.
Tauberian theorem was initially proved by Tauber [34] in 1897. Since then several mathematicians studied this theorem from different aspects. Some of them are Estrada and Vindas [12], Schmidt [33], Dik [9], Edely and Mursaleen [11], Braha [5] and Maddox [19]. In [15] Fridy and Khan proved certain Tauberian theorems via statistical convergence. Subsequently, Mòricz and Stadtmüller [23] prove necessary and sufficient Tauberian conditions under which convergence follows from summability by weighted mean. Recently Raj et al. [30] established some Tauberian theorems for Orlicz spaces of double difference sequences of fuzzy numbers. In several fields of mathematics, Tauberian theorems serve many applications. Likewise in the analysis of differential operators, complex analysis, number theory and probability theory (see [1, 18]). Raj and Choudhary [31] studied some applications of Tauberian theorems for Cesàro Orlicz double sequences.
A double sequence x = (xmn) is an infinite array of elements (or ) for all Bromwich [6] initiated the work on double sequences. Later on, the double sequences were studied by Moricz [21], Moricz and Rhoades [22], Başarir and Solankan [3], Tripathy et al. [39] and many others. Baliarsingh [2] studied some difference double sequence spaces of fractional order. In [26] Nayak and Baliarsingh explored some applications of double difference sequences. Recently, Choudhary and Raj [8] investigated some interesting results on the space of double difference sequences of fractional order. Ulusu and Gülle [41] worked on statistical convergence for double set sequences. Nuray et al. studied lacunary statistical convergence [27] and Cesàro summability [28] on double sequences of sets. A double sequence x = (xmn) is bounded if there exists a positive number k such that |xmn| < k, for all m and n. Let c, c0 and ℓ∞ denote the space of convergent, null and bounded sequences respectively.
Initially, Kızmaz [17] introduced difference sequence spaces. The notion was further generalized by Et and Çolak [13]. Let r be a non-negative integer and w denotes the set of real or complex sequences. Then for Z = c, c0 and ℓ∞, we have the following sequence spaces
where Δrx = (Δrxm) = (Δr-1xm - Δr-1xm+1) and Δ0xm = xm for all , which is equivalent to the following binomial representation
Similarly, difference operator on double sequences can be defined as:
and
Fuzzy set theory is an incredible tool for modelling uncertainty and vagueness in different issues emerging in the field of science and technology. This theory has wide range of applications in population dynamics, chaos control, computer programming and non-linear dynamical systems. In [42] Zadeh introduced the concept of a fuzzy number. For definitions and results on fuzzy numbers sequences one can refer to ([16, 40]). For applications in different fields, one can refer to [14] and [24]. Matloka [20] introduced the concept of usual convergence in fuzzy number sequences and Nanda [25] proved that the set of all convergent fuzzy number sequences form a complete metric space. Let F1 denotes the space of fuzzy numbers. For x ∈ F1, λ -level set [x] λ is defined by
The set [x] λ is closed, bounded and non-empty interval for each λ ∈ [0, 1] which is defined by [x] λ = [x- (λ) , x+ (λ)].
Definition 1.1. [4] Let
Then D is called the Hausdorff distance between fuzzy numbers x and y.
Proposition 1.2.[4] Let x, y, z, t ∈ F1 and Then the following hold:
(i) (F1, D) is a complete metric space.
(ii) D (x + z, y + z) = D (x, y) .
(iii) D (kx, ky) = |k|D (x, y) .
(iv) D (x + y, z + t) ≤ D (x, z) + D (y, t) .
(v)
Definition 1.3. A double sequence x = (xmn) of fuzzy numbers is a function x from into the set F1.
Definition 1.4. Let u = (ukl) be a double sequence of positive real numbers. A double sequence x = (xmn) of fuzzy numbers is said to be convergent to the fuzzy number L written as if for every ɛ > 0 there exists a positive integer n0 (ɛ) such that D (uklΔrxmn, L) < ɛ whenever m, n ≥ n0. The number L is called the Pringsheim limit of x.
Definition 1.5. A double sequence (xmn) is said to be summable to L if
where is a means of (xmn) and
for all non-negative integers m and n .
Definition 1.6. Let m and n be sufficiently large non-negative integers and for αn the integer part of the product αn . Then the de la Vallée Poussin means of the double sequence (xmn) are defined by
and
Tripathy and Baruah [36] initiated the study of the concept of slowly oscillating sequences of fuzzy numbers.
Definition 1.7. A double sequence (xmn) is said to be slowly oscillating in the sense (1, 1) , if
Identically, a double sequence (xmn) is slowly oscillating in the sense (1, 1) if for each ɛ > 0, there exists η1 (ɛ) and α = (αɛ) >1, such that D (uklΔrxkl, uklΔrxmn) ≤ ɛ, whenever η1 < m < k ≤ αm and η1 < n < l ≤ αn .
Definition 1.8. A double sequence (xmn) is said to satisfy the two-sided Hardy type Tauberian condition in the sense (1, 0) , if there exists a positive integer γ1 and a constant G such that
Definition 1.9. A double sequence (xmn) of fuzzy number is said to satisfy the two-sided Hardy type Tauberian condition in the sense (0, 1) , if there exists a positive integer δ1 and a constant G1 such that
Main results
Theorem 2.1.If x = (xmn) is bounded and convergent to L . Then x = (xmn) is summable to a fuzzy number L .
Proof. Let x = (xmn) be a double sequence of fuzzy number convergent to L ∈ F1 such that Now by using Proposition 1.2, we get
Since and also a double sequence (xmn) is bounded. Hence, by using the regularity of (C, 1, 1) summability, we have □
The following example explains that the converse of Theorem 2.1 does not hold in general.
Example 2.2. Define the double sequence of fuzzy numbers x = (xmn) by
where
and
Clearly, is not convergent. Now, we can check the endpoints of the λ-level set of uklΔrxmn.
and
Then by the definition of mean, we have
and
Hence, the sequences and converges to and as m, n→ ∞ respectively. Now by taking κν = (τν + 3ςν)/4, we get Thus, (xmn) is summable to κν . Therefore, we can conclude that a double sequence of fuzzy numbers (xmn) is summable but not convergent to κν.
Now, we show that if a double sequence of fuzzy numbers (xmn) is summable then it is convergent with the help of certain Tauberian conditions. These types of results are known as Tauberian Theorems. Firstly, we shall give some lemmas that help to prove Tauberian Theorems.
Lemma 2.3.Let Δr be a difference operator of order r . Then the followings hold:
(i) If α > 1, αm > m and αn > n, then
(ii) If 0 < α < 1, αm < m and αn < n, then
Proof.
(ii) Lemma 2.4.If x = (xmn) is summable to L, thenand
Proof. From Proposition 1.2, we have
Now, by using Lemma 2.3 (i) and (2.3) , we get
For all α > 1 and sufficiently large n, we have
The inequality (2.4) holds for αm with sufficiently large m . Thus, (2.1) follows from (1.1) and (2.4) . Similarly, we can prove for (2.2) .□
Theorem 2.5.Let Δr be a difference operator of order r . If x = (xmn) is summable to L, then x = (xmn) is convergent to L if and only if either of the following holds:
Proof. Firstly, we prove the direct part of the theorem. Since x = (xmn) is summable to a fuzzy number L and Then, we have
Now, by using (2.7) , we have (2.5) and (2.6) follows by (2.1) and (2.2) respectively.
Conversely, consider that (2.5) is satisfied. Hence, for any given ɛ > 0, there exists α0 > 1 such that
Also, we have
Since x = (xmn) is summable to L . Hence, by using (2.1) and (2.8) , we have
and if (2.6) is satisfied, for any given ɛ > 0, there exist 0 < α0 < 1 such that
Also,
and x = (xmn) is summable to L . Thus, by using (2.2) and (2.10) , we get
Theorem 2.6.If x = (xmn) is slowly oscillating in the sense (1, 1) and summable to L, then x = (xmn) is convergent to L .
Proof. Consider that a double sequence x = (xmn) is slowly oscillating. Since,
Hence, Now, by Theorem 2.5, (xmn) is convergent to L .□
Lemma 2.7.If x = (xmn) satisfies two-sided Tauberian condition of Hardy type in the senses (0, 1) and (1, 0) , then x = (xmn) is slowly oscillating in the sense (1, 1) .
Proof. Consider a double sequence x = (xmn) satisfies two-sided Tauberian conditions of Hardy type in the senses (1, 0) and (0, 1) . Then there exists a positive integer η1 = η1 (ɛ) and a constant G such that
and
whenever m, n > η1 . Now, we have
D (uklΔrxkl, uklΔrxmn)
for all 1 < η1 < m < k ≤ αm and 1 < η1 < n < l ≤ αn . Thus, we have D (uklΔrxkl, uklΔrxmn) ≤ ɛ, for each ɛ > 0, 1 < η1 < m < k ≤ αm and 1 < η1 < n < l ≤ αn .□
Theorem 2.8.If x = (xmn) is summable to a fuzzy number L and satisfies two-sided
Tauberian condition of Hardy type in the senses (1, 0) and (0, 1) , then (xmn) is convergent to L.
Proof. One can easily obtain the result by the consequence of Lemma 2.7 and Theorem 2.6 .□
Conclusion
In this paper, we have presented Tauberian theorems for (C, 1, 1)-summability method of double difference sequences of fuzzy numbers by using de la Vallée Poussin mean. We have investigated some interesting necessary and sufficient Tauberian conditions for double difference sequences of fuzzy numbers and obtain a relation between them. After studying this research paper, one can acquire Tauberian conditions for the statistical Cesàro summability method and the weighted Cesàro summability method on double fuzzy number sequences by using de la Vallée Poussin mean and double difference operator of order r . An application of Tauberian theorems for difference sequences bring out effective results in other fields of science and technology [10]. Tauberian theorems are useful in handling multicomponent gas diffusion. These theorems help to get a solution of the Cauchy problem for free Schrödinger equation in the norms of different Banach spaces and are also helpful in stabilizing the solutions of the Cauchy problem for the heat kernel equation.
Availability of data and material
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Funding
Not applicable.
Authors contributions
The authors contributed equally and significantly in writing this paper. All authors read and approved the final manuscript.
Footnotes
Acknowledgment
Dr. Kuldip Raj thanks the Council of Scientific and Industrial Research (CSIR), India for partial support under Grant No. 25(0288)/18/EMR-II, dated 24/05/2018. The authors are very thankful to referees for carefully reading the manuscript and for their valuable suggestions which improved the presentation of the paper.
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