Search

To reduce a fuzzy automaton into equivalent minimal automaton is a challenging issue related to fuzzy finite automata theory. The state minimization and state reduction techniques are used to convert fuzzy automata into equivalent fuzzy automata. For state minimization of fuzzy automaton, two identical states are merged to obtain a smaller equivalent automaton and for state reduction indistinguishable states are merged to find a relative smaller automaton. This paper reviews different methods used for state minimization and state reduction of fuzzy automata over complete residuated lattice. [ABSTRACT FROM AUTHOR]

Automata theory is study of mathematical properties of abstract computing machine. One of the applications of finite automata is lexical analysis. Researchers proposed rough finite state automata or fuzzy automata as recognizer that accepts imprecise languages. It defines formal languages and decides if any string belongs to the language or not. We have proposed rough fuzzy (final) automata model in this article. This model recognizes rough fuzzy (final) languages. It is suitable as a lexical analyzer when the decision values are fuzzy or can be converted to fuzzy. [ABSTRACT FROM AUTHOR]

Fuzzy approach has been applied to automata theory to obtain fuzzy automaton in the very early age of fuzzy set theory. Fuzzy automaton is the mathematical model, recognizing fuzzy regular languages. Myhill-Nerode theorem for finite automaton is a very powerful tool for minimizing the number of states in a finite automaton. Interval-valued fuzzy automaton is one of the generalized fuzzy automata. In this paper, an extension of Myhill-Nerode theorem for Interval-valued fuzzy regular language is established. Also, the problem of minimizing the finite automaton with Interval-valued fuzzy (final) states is explored. [ABSTRACT FROM AUTHOR]

We propose a compositional modeling framework for Mixed Reality (MR) software architectures in order to express, simulate and validate formally the real-time properties of such systems. Our approach is first based on a functional decomposition of such systems into generic components. The obtained elements as well as their typical interactions give rise to generic representations in terms of timed automata. A whole application is then obtained as a composition of such defined components. The approach is illustrated on a case study modeled by timed automata synchronizing through channels and including a large number of time constraints. This system has been simulated in UPPAAL and checked against basic behavioral properties. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive fuzzy hysteresis band current controller for four-wire shunt active power filters to eliminate harmonics and to compensate reactive power in distribution systems in order to keep currents at the point of common coupling sinusoidal and in phase with the corresponding voltage and the cancel neutral current. The conventional hysteresis band known for its robustness and its advantage in current controlled applications is adapted with a fuzzy logic controller to change the bandwidth according to the operating point in order to keep the frequency modulation at tolerable limits. The algorithm used to identify the reference currents is based on the synchronous reference frame theory (dqγ). Finally, simulation results using Matlab/Simulink are given to validate the proposed control. [ABSTRACT FROM AUTHOR]

We present a new method for the recognition of handwritten Arabic words based on neuro-fuzzy hybrid network. As a first step, connected components (CCs) of black pixels are detected. Then the system determines which CCs are sub-words and which are stress marks. The stress marks are then isolated and identified separately and the sub-words are segmented into graphemes. Each grapheme is described by topological and statistical features. Fuzzy rules are extracted from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data using a fuzzy c-means, and rule parameter tuning phase using gradient descent learning. After learning, the network encodes in its topology the essential design parameters of a fuzzy inference system. The contribution of this technique is shown through the significant tests performed on a handwritten Arabic words database. [ABSTRACT FROM AUTHOR]

In this work, we give three isomorphism theorems of fuzzy soft groups by using the concepts of kernel and image of fuzzy soft homomorphism of fuzzy soft groups. [ABSTRACT FROM AUTHOR]

In this paper an application of Fuzzy Logic for Automatic Braking system is proposed. Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal Depending upon the speed and distance of train. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance depending upon the varying speed and distance of the train. [ABSTRACT FROM AUTHOR]