The use of Recurrent Neural Networks is not as extensive as Feedforward Neural Networks.
Training algorithms for Recurrent Neural Networks, based on the error gradient, are very …

Automata are the prime example of general computational systems over discrete spaces.
The incorporation of fuzzy logic into automata theory resulted in fuzzy auotomata which can …

Approximate bisimulations for fuzzy automata have recently drawn attention of researches,
since they allow to correlate different fuzzy automata which behave equivalently only to the …

Purpose–Conventional rule‐based systems are insufficient for description of complex
dynamic systems requiring nontrivial decision procedures. Fuzzy cognitive maps seem to be …

Simulations and bisimulations are well-established notions in crisp/fuzzy automata theory
and are widely used to compare the behaviors of automata. Their main drawback is that they …

This paper deals with the experimental study and comparison of various adaptation methods
for setting-up parameters of fuzzy cognitive maps (FCMs). A survey is given of the best …

The application of neural networks to solve a problem involves tasks with a high
computational cost until a suitable network is found, and these tasks mainly involve the …

Grammatical inference has been extensively studied in recent years as a result of its wide
field of application, and in turn, recurrent neural networks have proved themselves to be a …

In this paper we provide further improvements of determinization methods for fuzzy finite
automata. These methods perform better than all previous determinization methods for fuzzy …

Classical automata theory cannot deal with the system uncertainty. To deal with the system
uncertainty the concept of fuzzy finite automata was proposed. Fuzzy automata can be used …