This paper proposes a novel adaptive fuzzy decentralized output-feedback control approach for a class of uncertain nonlinear large-scale systems. The considered nonlinear systems possess the unknown nonlinear functions, unmeasured states and unknown time-varying delays. Fuzzy logic systems are employed to approximate the unknown nonlinear functions, and adaptive high-gain filters are presented ...

ـــــ In [25], we introduce the notion of r-fuzzy neighborhood filters in smooth topological spaces in sense of Gähler [10], and used it to define and study separation axioms , = , , . Here we continue our study of the axioms of separation in smooth topological spaces. Therefore, we introduce the notion of r-fuzzy neighborhood filter at a set. Then by using this notion we define and study separ...

This paper presents a novel fuzzy energy minimization method for simultaneous segmentation and bias field estimation of medical images. We first define an objective function based on a localized fuzzy c-means (FCM) clustering for the image intensities in a neighborhood around each point. Then, this objective function is integrated with respect to the neighborhood center over the entire image do...

In this paper, the concepts of derived sets and derived operators are generalized to $(L, M)$-fuzzy topological spaces and their characterizations are given.What is more, it is shown that the category of stratified $(L, M)$-fuzzy topological spaces,the category of stratified $(L, M)$-fuzzy closure spaces and the category of stratified $(L, M)$-fuzzy quasi-neighborhood spaces are all isomorphic ...

Experts in machine learning and fuzzy system frequently identify understanding the data with the use of logical rules. Reasons for inadequacy of crisp and fuzzy rule-based explanations are presented. An approach based on analysis of probabilities of classification p(Ci|X;ρ) as a function of the size of the neighborhood ρ of the given case X is presented. Probabilities are evaluated using Monte ...

A theory of granular computing is presented. Some classical example are examined to obtain the hint of new directions Obvious examples are dynamic programming, fuzzy numbers, infinitesimal number and access control model, (pre)topological spaces are examined; Localized multi-level granulation can be modeled by generalized topological spaces, called neighborhood systems. For most general granula...

In this paper we introduce the notion of fuzzy bitopological ideals .The concept of fuzzy pairwise local function is also introduced here by utilizing the q-neighborhood structure for a fuzzy topological space .These concepts are discussed fuzzy bitopologies and several relations between different fuzzy bitopological ideals .

The main purpose of this paper is to achieve improvement in thespeed of Fuzzy Joint Points (FJP) algorithm. Since FJP approach is a basisfor fuzzy neighborhood based clustering algorithms such as Noise-Robust FJP(NRFJP) and Fuzzy Neighborhood DBSCAN (FN-DBSCAN), improving FJPalgorithm would an important achievement in terms of these FJP-based meth-ods. Although FJP has many advantages such as r...

We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy ...