Research Article

f-rough Cauchy sequences


Abstract

In this article, we narrated the new notion of rough f-statistical convergence and rough f-statistical Cauchy sequences, successively becoming a more generalized version of rough statistical convergence and rough statistical Cauchy sequences. Consecutively, compare the following important theorems with those of Listán-García [Quaest. Math. 37(4) (2014), 525–530], Phu [Numer. Funct. Anal. Optim. 22(1–2) (2001), 199–222 and Numer. Funct. Anal. Optim. 24(3–4) (2003), 285–301], and Aytar [Numer. Funct. Anal. Optim. 29(3–4) (2008), 291–303].

Suppose x = {xn } n ∈ℕ is a bounded sequence in some finite dimensional normed space X. Let C denote the cluster point set of this sequence. Then, DX (C) is the minimal Cauchy degree and rX (C) is the minimal convergence degree of {xn } n ∈ℕ, where

That means is a ρ-Cauchy sequence}, and

Suppose ρ ≥ 0 and {xn } n ∈ℕ is a ρ-Cauchy sequence in some normed space X. Then, {xn } n ∈ℕ is r-convergent for every r > 2−1 J(X)ρ. If X is finite dimensional then {xn } n ∈ℕ is r-convergent for every r ≥ 2−1 J(X)ρ.

If x = {xn } n ∈ℕ is a sequence in a finite dimensional normed space ℝ n , then

If we reformulate the above three results regarding rough f -statistical convergence and rough f -statistical Cauchy sequences in an infinite dimensional normed space, subsequent assertions will be false. Apart from these, we find the minimal f -statistical convergence degree and the minimal f -statistical Cauchy degree of a sequence in any dimensional normed spaces.

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