In this paper, we study the concept of statistical convergence on L?fuzzy normed spaces. Then give a useful characterization for statistically convergent sequences. Furthermore, illustrate that our method is more general than usual

Cesàro statistical convergence in neutrosophic normed spaces is investigated this research. Additionally, study, we concentrate at several features of NNS such as concepts statistically Cauchy, convergent Cauchy.

Markov Random Fields (MRF) minimization is a well-known problem in computer vision. We consider the augmented dual of the MRF minimization problem and develop a Mirror Descent algorithm based on weighted Entropy and Euclidean Projection. The augmented dual problem consists of maximizing a non-differentiable objective function subject to simplex and linear constraints. We analyze the convergence...

The statistical unbounded topological convergence was studied and investigated with respect to the solid topology in locally Riesz spaces. In this paper, we introduce order spaces by developing a topology-free technique on Moreover, give some relations other kinds of convergences.