A new rough-fuzzy model for pattern classification based on granular computing is described in the present article. In this model, we propose the formulation of class-dependent granules in fuzzy environment. Fuzzy membership functions are used to represent the feature-wise belonging to different classes, thereby producing fuzzy granulation of the feature space. The fuzzy granules thus generated...

In this paper,  fuzzy convergence theory in the framework of $L$-convex spaces is introduced. Firstly, the concept of $L$-convex remote-neighborhood spaces is introduced and it is shown that the  resulting category is isomorphic to that of $L$-convex spaces. Secondly, by means of $L$-convex ideals, the notion of $L$-convergence spaces is introduced and it is proved that the  category of $L$-con...

|The problem of assigning labels to objects given some relational constraints is occuring quite often in the eld of pattern recognition. Among the diierent solutions proposed there is a particularly successful one: Relaxation labeling. Relaxation labeling has turned out to be a useful iterative scheme for parallel information integration forcing neighborhood constraint satisfaction. Consequentl...

This paper focuses on the problem of direct adaptive fuzzy control for nonlinear strict-feedback systems with time-varying delays. Based on the Razumikhin function approach, a novel adaptive fuzzy controller is designed. The proposed controller guarantees that the system output converges to a small neighborhood of the reference signal and all the signals in the closed-loop system remain bounded...

This paper is concerned with the problem of adaptive fuzzy output tracking for a class of perturbed strict-feedback nonlinear systems with time delays and unknown virtual control coefficients. Fuzzy logic systems in Mamdani type are used to approximate the unknown nonlinear functions, then the adaptive fuzzy tracking controller is designed by using the backstepping technique and Lyapunov–Krasov...

This paper introduces an improved electromagnetism-like algorithm (IEM) for recurrent fuzzy neural controller design. The hybrid IEM algorithm combines the advantages of the electromagnetism-like (EM) algorithm and the genetic algorithm (GA). The proposed IEM is composed of initialization, local search, total force calculation, movement, and evaluation. For recurrent fuzzy neural controller des...

In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly p...

In this paper, an adaptive fuzzy output feedback control approach with prescribed performance is proposed for a class of uncertain nonlinear strict-feedback systems with unmeasured states. With the help of fuzzy logic systems identifying the unknown nonlinear system, a fuzzy state observer is established for estimating the unmeasured states. Under the framework of the backstepping control desig...

The purpose of this paper is to study soft sets and soft topological spaces. We also introduce the concepts of soft interior point, soft interior, soft neighborhood, soft continuity and soft compactness. The relationships between soft topology and fuzzy topology are also provided. Also, some basic properties of these concepts are explored. 2010 AMS Classification: 06D72, 54A40