The aim of this paper is to obtain a common fixed point theorem in an intuitionistic fuzzy metric space for pointwise R-weakly commuting mappings using contractive condition of integral type and to establish a situation in which a collection of maps has a fixed point which is a point of discontinuity.

In this paper we derive maximal pointwise Hölder estimates for the Kohn’s Laplacian on strongly pseudoconvex CR manifolds of class C3 using the Tanaka-Webster Pseudohermitian metric. The estimates can be used to improve the Boutet De Monvel’s embedding theorem for strongly pseudoconvex compact CR manifolds of real dimension greater or equal to five with less smoothness assumption.

Let B be the closed unit ball in R and S its boundary. We define a family of pseudo metrics on B. As an application, we prove that for any countable-to-one function f : S → [0, a], the set NMnf = {x ∈ S 2 | there exists y ∈ S2 such that f(x)−f(y) > ndE(x, y)} is uncountable for all n ∈ N, where dE is the Euclidean metric on R . 2000 Mathematics Subject Classification ; 57N05, 57M40 1 The family...

There are presented the basic operations on real intervals: pseudo-addition and pseudo multiplication which induce the semiring structure. Application of special pseudo-operations on the unit interval: t-norms and t-conorms, in the theory of fuzzy sets and fuzzy logics are given. Pseudo-convolution as a generalization of the classical convolution is given, with many important special cases. Fur...

In this paper, we prove that every topological space is a sequence-covering image of a metric space, which answers a question on pseudo-sequence-covering images of metric spaces.

A new distance function for fuzzy sets is introduced. It is based on the descriptive complexity, that is, the number of bits (on average) that are needed to describe an element in the symmetric difference of the two sets. The value of the distance gives the amount of additional information needed to describe either one of the two sets when the other is known. We prove that the distance function...

Motivated by recent developments in manifold-valued regression we propose a family of nonparametric kernel-smoothing estimators with metric-space valued output including several robust versions. Depending on the choice of the output space and the metric the estimator reduces to partially well-known procedures for multi-class classification, multivariate regression in Euclidean space, regression...