Learning Fuzzy Automaton's Event Transition Matrix When Post-Event State Is Unknown

Compared to other system modeling techniques, the fuzzy discrete event systems (FDESs) methodology has the unique capability of modeling a class of event-driven systems as fuzzy automata with ambiguous state and event-invoked state transition. In two recent papers, we developed algorithms for online...

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Vydané v:	IEEE transactions on cybernetics Ročník 52; číslo 6; s. 4993 - 5000
Hlavní autori:	Ying, Hao, Lin, Feng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Automata Computer simulation Discrete event systems Fuzzy automata fuzzy discrete event systems (FDESs) Fuzzy sets Fuzzy systems Learning automata Machine learning Mathematical model Medical services Modelling stochastic gradient descent supervised learning
ISSN:	2168-2267, 2168-2275, 2168-2275
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