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Volumn 9, Issue 3, 1998, Pages 571-575

Inductive inference from noisy examples using the hybrid finite state filter

Author keywords

Finite state automata; Grammatical inference; Iterated function systems; Recurrent neural networks

Indexed keywords

ADAPTIVE SYSTEMS; COMPUTATIONAL GRAMMARS; FINITE AUTOMATA; ITERATIVE METHODS; LEARNING ALGORITHMS; OPTIMIZATION;

EID: 0032074270     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.668898     Document Type: Article
Times cited : (19)

References (11)
  • 1
    • 84953506049 scopus 로고
    • Extraction, insertion, and refinement of symbolic rules in dynamically driven recurrent neural networks
    • Connection Sci.
    • C. L. Giles and C. W. Omlin, "Extraction, insertion, and refinement of symbolic rules in dynamically driven recurrent neural networks," Connection Sci., special issue on architectures for integrating symbolic and neural processes, vol. 5, nos. 3/4, p. 307, 1993.
    • (1993) Architectures for Integrating Symbolic and Neural Processes , vol.5 , Issue.3-4 SPEC. ISSUE , pp. 307
    • Giles, C.L.1    Omlin, C.W.2
  • 2
    • 0001601299 scopus 로고
    • Induction of finite-state languages using second-order recurrent networks
    • May
    • R. L. Watrous and G. M. Kuhn, "Induction of finite-state languages using second-order recurrent networks," Neural Computa., vol. 4, pp. 406-414, May 1992.
    • (1992) Neural Computa. , vol.4 , pp. 406-414
    • Watrous, R.L.1    Kuhn, G.M.2
  • 4
    • 0030125824 scopus 로고    scopus 로고
    • Representation of finite-state automata in recurrent radial basis function networks
    • P. Frasconi, M. Gori, M. Maggini, and G. Soda, "Representation of finite-state automata in recurrent radial basis function networks," Machine Learning, vol. 23, pp. 5-32, 1996.
    • (1996) Machine Learning , vol.23 , pp. 5-32
    • Frasconi, P.1    Gori, M.2    Maggini, M.3    Soda, G.4
  • 5
    • 0001949873 scopus 로고
    • Recurrent networks: State machines or iterated function systems?
    • M. C. Mozer, P. Smolensky, D. S. Touretzky, J. L. Elman, and A. S. Weigend, Eds. Hillsdale, NJ: Lawrence Erlbaum
    • J. F. Kolen, "Recurrent networks: State machines or iterated function systems?," in Proc. 1993 Connectionist Models Summer School, M. C. Mozer, P. Smolensky, D. S. Touretzky, J. L. Elman, and A. S. Weigend, Eds. Hillsdale, NJ: Lawrence Erlbaum, 1994, pp. 203-210.
    • (1994) Proc. 1993 Connectionist Models Summer School , pp. 203-210
    • Kolen, J.F.1
  • 6
    • 0030586641 scopus 로고    scopus 로고
    • The dynamics of discrete-time computation, with the application to recurrent neural networks and finite-state machine extraction
    • M. Casey, "The dynamics of discrete-time computation, with the application to recurrent neural networks and finite-state machine extraction," Neural Computa., vol. 8, no. 6, pp. 1135-1178, 1996.
    • (1996) Neural Computa. , vol.8 , Issue.6 , pp. 1135-1178
    • Casey, M.1
  • 7
    • 0001257629 scopus 로고
    • Experimental comparison of the effect of order in recurrent neural networks
    • applications of neural networks to pattern recognition
    • C. B. Miller and C. L. Giles, "Experimental comparison of the effect of order in recurrent neural networks," Int. J. Pattern Recognition Artificial Intell., special issue on applications of neural networks to pattern recognition, vol. 7, no. 4, pp. 849-872, 1993.
    • (1993) Int. J. Pattern Recognition Artificial Intell. , vol.7 , Issue.4 SPEC. ISSUE , pp. 849-872
    • Miller, C.B.1    Giles, C.L.2
  • 8
    • 0030083072 scopus 로고    scopus 로고
    • Rule revision with recurrent neural networks
    • C. W. Omlin and C. L. Giles, "Rule revision with recurrent neural networks," IEEE Trans. Knowledge Data Eng., vol. 8, no. 1, p. 183, 1996.
    • (1996) IEEE Trans. Knowledge Data Eng. , vol.8 , Issue.1 , pp. 183
    • Omlin, C.W.1    Giles, C.L.2
  • 9
    • 0001609567 scopus 로고
    • An efficient gradient-based algorithm for on-line training of recurrent network trajectories
    • R. J. Williams and J. Peng, "An efficient gradient-based algorithm for on-line training of recurrent network trajectories," Neural Computa., vol. 2, no. 4, pp. 490-501, 1990.
    • (1990) Neural Computa. , vol.2 , Issue.4 , pp. 490-501
    • Williams, R.J.1    Peng, J.2
  • 10
    • 84947426484 scopus 로고
    • Second-order recurrent neural networks can learn regular grammars from noisy strings
    • From Natural to Artificial Neural Computa.: Proc. IWANN'95 (June 7-9, 1995), J. Mira and F. Sandoval, Eds., New York: Springer-Verlag
    • R. C. Carrasco and M. L. Forcada, "Second-order recurrent neural networks can learn regular grammars from noisy strings," in From Natural to Artificial Neural Computa.: Proc. IWANN'95 (June 7-9, 1995), J. Mira and F. Sandoval, Eds., vol. 930 of Lecture Notes in Computer Science. New York: Springer-Verlag, 1995, pp. 605-610.
    • (1995) Lecture Notes in Computer Science , vol.930 , pp. 605-610
    • Carrasco, R.C.1    Forcada, M.L.2
  • 11
    • 0001770758 scopus 로고
    • Dynamic construction of finite-state automata from examples using hill-climbing
    • Ann Arbor, MI
    • M. Tomita, "Dynamic construction of finite-state automata from examples using hill-climbing," in Proc. 4th Annu. Cognitive Sci. Conf., Ann Arbor, MI, 1982, pp. 105-108.
    • (1982) Proc. 4th Annu. Cognitive Sci. Conf. , pp. 105-108
    • Tomita, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.