Computation and automata
Learning automata: an introduction
Learning automata: an introduction
Neural network learning and expert systems
Neural network learning and expert systems
Artificial Intelligence and Neural Networks; Steps toward Principled Integration
Artificial Intelligence and Neural Networks; Steps toward Principled Integration
Fault Detection and Diagnosis of Manipulator Based on Probabilistic Production Rule
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Language identification of controlled systems: modeling, control, and anomaly detection
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
On learning context-free and context-sensitive languages
IEEE Transactions on Neural Networks
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Formal language techniques may be used to study controlled dynamical systems and lead to a formulation in terms of context-dependent grammars. Using automata as basic units we obtain an on-line implementation of the grammars. The implementation has a hierarchical structure, the lowest level dealing with the identification of alphabet symbols (terminal and non-terminal), and the other with the establishment of the grammar productions. The method provides an automatic construction of the automata network from the experimental data. In particular, the parallel-processing capabilities of automata networks improves the performance of grammar-based models for control and anomaly detection in electromechanical devices of industrial relevance. One such example is presented.