We de ne robust timed automata, which are timed automata that accept all trajectories \robustly": if a robust timed automaton accepts a trajectory, then it must accept neighboring trajectories also; and if a robust timed automaton rejects a trajectory, then it must reject neighboring trajectories also. We show that the emptiness problem for robust timed automata is still decidable, by modifying...

Using hybrid automata, one is able to model many types of systems and express their properties in various formal languages. Being extremely general and rich, however, the class of hybrid automata exhibits the inherent problems of automata theory: even the simplest of properties for general hybrid automata are undecidable. Therefore, one must restrict attention only to subclasses of this very ge...

INTRODUCTION The concept of fuzzy sets introduced by Zadeh [19], was the foundation of fuzzy metric space. Fuzzy metric spaces have been introduced by Kramosil and Michalek [8] and George and Veeramani [3] modified the notion of fuzzy metric spaces with the help of continuous tnorm. Recently many authors such as [4], [7], [14] and [15] have proved fixed point theorems involving fuzzy sets. Bouh...

In previous studies we first concentrated on utilizing crisp simulationto produce discrete event fuzzy systems simulations. Then we extendedthis research to the simulation of continuous fuzzy systems models. In this paperwe continue our study of continuous fuzzy systems using crisp continuoussimulation. Consider a crisp continuous system whose evolution depends ondifferential equations. Such a ...

In this paper, by using operations, some characterizations and some properties of fuzzy lower and upper continuous multifunctions and its weaker and stronger forms including fuzzy lower and upper weakly continuous, fuzzy lower and upper θ-continuous, fuzzy lower and upper strongly θ-continuous, fuzzy lower and upper almost strongly θ-continuous, fuzzy lower and upper weakly θ-continuous, fuzzy ...

Abstract: In this paper we present the Beta function and its main properties. A key feature of the Beta function, which is given by the central-limit theorem, is also shown. We then introduce a new category of neural networks based on a new kernel: the Beta function. Next, we investigate the use of Beta fuzzy basis functions for the design of fuzzy logic systems. The functional equivalence betw...