In this paper, we introduce and study the concepts of $mathcal{I}_2$-convergence, $mathcal{I}_2^{*}$-convergence for double sequences of fuzzy real numbers, where $mathcal{I}_2$ denotes the ideal of subsets of $mathbb N times mathbb N$. Also, we study some properties and relations of them.

Let A = (a jn) be an infinite summability matrix. For a given sequence x := (xn), the A-transform of x, denoted by Ax := ((Ax) j), is given by (Ax) j = ∑n=1 a jnxn provided the series converges for each j ∈ N, the set of all natural numbers. We say that A is regular if limAx = L whenever limx = L [4]. Assume that A is a non-negative regular summability matrix. Then x = (xn) is said to be A-stat...

‎in this paper‎, ‎an approach based on statistical spline model (ssm) and collocation method is proposed to solve volterra-fredholm integral equations‎. ‎the set of collocation nodes is chosen so that the points yield minimal error in the nodal polynomials‎. ‎under some standard assumptions‎, ‎we establish the convergence property of this approach‎. ‎numerical results on some problems are given...

the purpose of this paper is to generalize the concepts of statisticalconvergence of sequences of fuzzy numbers defined by a modulus functionusing difference operator $delta$ and give some inclusion relations.

In this paper, we introduce the concepts of weighted ideal statistical convergence or SN (I)-convergence and I − (N, pn)-summability. We also establish the relations between our new methods. Further, we determine a Korovkin type approximation theorem through I − (N, pn)-summability. −−−−−−−−−−−−−−−−−−−−−−−−−−−−

In this paper, we introduce the notions of [V,λ ]-summability and λ−statistical convergence of function by taking a nonnegative real-valued Lebesque measurable function in the interval (1,∞) and introduce new notions, namely, [V,λ ] (I )− summability, and Iλ−statistical convergence of function. We mainly examine the relation between these two new methods.

In this paper, we investigate the convergence of a sequence of minimizing trajectories in infinite horizon optimization problems. The convergence is considered in the sense of ideals and their particular case called the statistical convergence. The optimality is defined as a total cost over the infinite horizon.