the object of this paper is to introduce the notion of intuitionisticfuzzy continuous mappings and intuitionistic fuzzy bounded linear operatorsfrom one intuitionistic fuzzy n-normed linear space to another. relation betweenintuitionistic fuzzy continuity and intuitionistic fuzzy bounded linearoperators are studied and some interesting results are obtained.

Let n ≥ 3. From the description of subdirectly irreducible complemented Arguesian lattices with four generators given by Herrmann, Ringel and Wille it follows that the subspace lattice of an n-dimensional vector space over a finite field is generated by four elements if and only if the field is a prime field. By exhibiting a 5-element generating set we prove that the subspace lattice of an n-di...

Exploration of large and high-dimensional data sets is one of the main problems in data analysis. Self-organizing feature maps (SOFM) is a powerful technique for clustering analysis and data mining. Competitive learning in the SOFM training process focuses on finding a neuron that its weight vector is most similar to that of an input vector. SOFM can be used to map large data sets to a simpler,...

Abstract: In this paper, a numerical scheme based on variational iteration method is given. The proposed method is an approximate-analytical algorithm for solving a generalized non-homogeneous n-dimensional system of linear fuzzy differential equations 0 x(t) Ax Bx(t) f(t) x(0) x = + + , =   , where A and B are real n×n matrices and the initial condition 0 x is described by a vector made up o...

and Applied Analysis 3 with f 0 0 in a non-Archimedean space. It is easy to see that the function f x ax bx2 is a solution of the functional equation 1.8 , which explains why it is called additive-quadratic functional equation. For more detailed definitions of mixed type functional equations, we can refer to 26–47 . Definition 1.1 see 48 . Let X be a real vector space. A function N : X × R → 0,...

we prove a related fixed point theorem for n mappings which arenot necessarily continuous in n fuzzy metric spaces using an implicit relationone of them is a sequentially compact fuzzy metric space which generalizeresults of aliouche, et al. [2], rao et al. [14] and [15].

We have observed that the support vector clustering method proposed by Asa Ben Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik, (Journal of Machine Learning Research, (2001), 125–137) can provide cluster boundaries of arbitrary shape based on a Gaussian kernel abstaining from explicit calculations in the high-dimensional feature space. This allows us to apply the method to the training set...