Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloEncoding Nondeterministic Fuzzy Tree Automata into Recursive Neural Networks
Anno di pubblicazione2004
Formato-
Autore/iPetrosino Alfredo, Gori Marco
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AbstractFuzzy neural systems have been a subject of great interest in the last few years, due to their abilities to facilitate the exchange of information between symbolic and subsymbolic domains. However, the models in the literature are not able to deal with structured organization of information, that is typically required by symbolic processing. In many application domains, the patterns are not only structured, but a fuzziness degree is attached to each subsymbolic pattern primitive. The purpose of this paper is to show how recursive neural networks, properly conceived for dealing with structured information, can represent nondeterministic fuzzy frontier-to-root tree automata. Whereas available prior knowledge expressed in terms of fuzzy state transition rules are injected into a recursive network, unknown rules are supposed to be filled in by data-driven learning. We also prove the stability of the encoding algorithm, extending previous results on the injection of fuzzy finite-state dynamics in high-order recurrent networks.
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Pagine da1435
Pagine a1449
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RivistaIEEE transactions on neural networks
Attiva dal 1990 al 2011
Editore: Institute of Electrical and Electronics Engineers, - New York, NY
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 1045-9227
Titolo chiave: IEEE transactions on neural networks
Titolo proprio: IEEE transactions on neural networks
Titolo abbreviato: IEEE trans. neural netw.
Titoli alternativi:
  • Institute of Electrical and Electronics Engineers transactions on neural networks
  • Transactions on neural networks
  • Neural networks
Numero volume della rivista15-6
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Strutture CNR
  • ICAR — Istituto di calcolo e reti ad alte prestazioni
Moduli/Attività/Sottoprogetti CNR
  • ICT.P03.002.001 : Sistemi di Visione Real-Time
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Rivista ISIIEEE TRANSACTIONS ON NEURAL NETWORKS [09418J0]
Note