Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

[2] Karsten Lehmann and Rafael Peñaloza. The complexity of computing the behaviour of lattice automata on infinite trees. On the decidability status of fuzzy ALC with general concept inclusions. [4] Stefan Borgwardt and Rafael Peñaloza. Consistency reasoning in lattice-based fuzzy description logics. Context-dependent views to axioms and consequences of semantic web ontologies. Classifying soft...

In this paper, we introduce generalized directable fuzzy automaton and discuss their structural characterizations. We have shown that a generalized directable fuzzy automaton is an extension of a uniformly monogenically strongly directable fuzzy automaton by a uniformly monogenically trap-directable fuzzy automaton and obtain other equivalent conditions for a generalized directable fuzzy automa...

Timed automata theory is well developed in literature. This theory provides a formal framework to model and test real-time systems. This formal framework supplies a way to describe transitions among states with timing constrains. These constraints are usually expressed with logic formulas involving the system clocks. The time domain of these clocks usually is considered dense, that is, the cloc...

Genetic algorithms are powerful tools that allow engineers and scientists to find good solutions to hard computational problems using evolutionary principles. The classic genetic algorithm has several disadvantages, however. Foremost among these drawbacks is the difficulty of choosing optimal parameter settings. Genetic algorithm literature is full of empirical tricks, techniques, and rules of ...

In 1965, in his pioneer paper L.A. Zadeh [9] introduced the concept of fuzzy set to handle the uncertainties in our daily life. After that many generalizations of fuzzy sets are presented, for example, interval valued fuzzy sets [10] and intuitionistic fuzzy sets [1]. Fuzzy sets are extremely useful to solve many problems in applied mathematics, information sciences and theory of automata [2]. ...

There has been an increased interest in combining fuzzy systems with neural networks because fuzzy neural systems merge the advantages of both paradigms. On the one hand, parameters in fuzzy systems have clear physical meanings and rule-based and linguistic information can be incorporated into adaptive fuzzy systems in a systematic way. On the other hand, there exist powerful algorithms for tra...

Each fuzzy set can be represented by a nested system of ordinary sets—its a-cuts. There is an extensive literature on fuzzy sets devoted to problems of the following kind: is it possible to reduce operations with fuzzy sets to operations with their a-cuts? Is it possible to reduce properties of fuzzy relations to properties of their a-cuts? More generally, can a fuzzy concept be represented by ...

The present paper has been an attempt to investigate the general fuzzy automata on the basis of complete residuated lattice-valued ($L$-GFAs). The study has been chiefly inspired from the work by Mockor cite{15, 16, 17}. Regarding this, the categorical issue of $L$-GFAs has been studied in more details. The main issues addressed in this research include: (1) investigating the relationship betwe...