Since the T-S fuzzy system can approximate any nonlinear system with arbitrary accuracy, it is also expected to be a suitable approach to observe the states of a stochastic nonlinear system. Up to date, a few state estimators for stochastic T-S fuzzy systems have been proposed and applied to various fields without rigorous proof. In this paper, we first derive a sufficient condition based on th...

In this work, three topics which are important for the further development of fuzzy systems are chosen to be investigated. First, the mathematical aspects of fuzzy relational equations (FREs) are explored. Solving FREs is one of the most important problems in fuzzy systems. In order to identify the algebraic information of the fuzzy space, two new tools, called fuzzy multiplicative inversion an...

In this paper, stability analysis of the PDCbased Takagi-Sugeno (T-S) fuzzy impulsive control systems by using the extended Lyapunov stability theory is investigated. Some sufficient conditions and criterions are derived for stability of T-S fuzzy impulsive control system in terms of linear matrix inequalities (LMIs). Finally, control schemes are successfully applied to stabilize a predator-pre...

This paper develops a general analysis and design theory for nonlinear time-varying systems represented by impulsive T-S fuzzy control model, which extends conventional T-S fuzzy model. In the proposed, model impulse is viewed as control input of T-S model, and impulsive distance is the major controller to be designed. Several criteria on general stability, asymptotic stability, and exponential...

Finite state automata are crucial for numerous practical algorithms of computer science. We show how to use genetic algorithms and fuzzy automata to simplify a class of FSA defined by labeled graphs and considered in the literature. Finite state automata, FSA, are well-known tools used in coding theory, text processing, image analysis and compression, speech recognition, and bioinformatics. Lab...

In [23], Zadeh introduced the notion of fuzzy sets and fuzzy set operations. Since then, fuzzy set theory developed by Zadeh and others has evoked great interest among researchers working in different branches of mathematics. Semirings play an important role in studying matrices and determinants. Many aspects of the theory of matrices and determinants over semirings have been studied by Beasley...

-Fuzzy set theory has found a promising field of application in the domain of digital image processing, since fuzziness is an intrinsic property of images. For dealing with spatial information in this framework from the signal level to the highest decision level, several attempts have been made to define mathematical morphology on fuzzy sets. The purpose of this paper is to present and discuss ...

Let I = ([0; 1];_;^; 0; 1), where _ and ^ are max and min, respectively. This algebra is the basic building block of fuzzy set theory and logic. Likewise, the algebra I = ([0; 1];_;^; 0; 1), where [0; 1] = f(a; b) : a; b 2 [0; 1], a bg, _, ^ are given coordinate-wise, and 0 and 1 are the bounds on [0; 1], is the relevant algebra for interval-valued fuzzy set theory and logic. A good share of th...

in this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the takagi-sugeno (t-s) fuzzy models is considered. a novel linear matrix inequality (lmi)-based stability criterion is obtained by using lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...