1 This paper describes DANIELA, a Neuro-Fuzzy system for control applications. The system is based on a custom neural device that can implement either Multi-Layer Perceptrons, Radial Basis Functions or Fuzzy paradigms. The system implements intelligent control algorithms mixing neuro-fuzzy algorithms with nite state automata and is used to control a walking hexapod.

 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 ...

Weighted automata generalize a number of concepts found in discrete event dynamics systems of various kind. Semirings are used as a base algebra for describing weights which implies a variety different interpretations for particular application cases. In this project, we want to explore how theoretical results in fact boil down to algorithms and techniques that work in practice. The goal of thi...

In this paper we combine determinization and state reduction methods into two-in-one algorithms that simultaneously perform determinization and state reduction. These algorithms perform better than all previous determinization algorithms for fuzzy finite automata, developed by Bělohlávek [Inform Sciences 143 (2002) 205–209], Li and Pedrycz [Fuzzy Set Syst 156 (2005) 68–92], Ignjatović et al. [I...

Fuzzy cellular automata (FCA) are cellular automata where the local rule is defined as the “fuzzification" of the local rule of the corresponding Boolean cellular automaton in disjunctive normal form. In this paper we are interested in two separate issues: the relationship between Boolean and fuzzy models, and the asymptotic behavior of elementary fuzzy cellular automata. On the first issue, we...

In this paper we show that the problem of minimizing a nonlinear objective function subject to a system of fuzzy relational equations with max-min composition can be reduced to a 0-1 mixed integer programming problem. The reduction method can be extended to the case of fuzzy relational equations with max-T composition as well as those with more general composition.

New types of systems of fuzzy relation inequalities and equations, called weakly linear, have been recently introduced in [J. Ignjatović, M. Ćirić, S. Bogdanović, On the greatest solutions to weakly linear systems of fuzzy relation inequalities and equations, Fuzzy Sets and Systems 161 (2010) 3081–3113.]. The mentioned paper dealt with homogeneous weakly linear systems, composed of fuzzy relati...

Elimination of redundancies in the memory representation is necessary for fast and efficient analysis of large sets of fuzzy data. In this work, we use MTBDDs as the underlying data-structure to represent fuzzy sets and binary fuzzy relations. This leads to elimination of redundancies in the representation, less computations, and faster analyses. We also extended a BDD package (BuDDy) to suppor...

Keywords: Fuzzy variable Independence Operation t-norm Convergence Law of large numbers a b s t r a c t T-independence of fuzzy variables is a more general concept than the classical independence. The objective of this study is to deal with some new properties of T-independent fuzzy variables. First of all, for any general t-norm, some criteria of T-independence are discussed for fuzzy variable...