Statistical convergence of multiple sequences

TLDR: In this article, the authors extend the concept of convergence from single sequences to multiple sequences of real or complex numbers and obtain the following result: the Fourier series of f is statistically convergent to $f ({\bf t})$ uniformly on the d-dimensional torus.

Abstract: We extend the concept of and basic results on statistical convergence from ordinary (single) sequences to multiple sequences of (real or complex) numbers. As an application to Fourier analysis, we obtain the following Theorem 3: (i) If $f \in L(\textrm{log}^{+} L)^{d-1}(\mathbb{T}^d)$, where $\mathbb{T}^d := [-\pi, \pi)^{d}$ is the d-dimensional torus, then the Fourier series of f is statistically convergent to $f({\bf t})$ at almost every ${\bf t} \in \mathbb{T}^d$; (ii) If $f \in C(\mathbb{T}^d)$, then the Fourier series of f is statistically convergent to $f ({\bf t})$ uniformly on $\mathbb{T}^d$.