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Volumn 2, Issue , 1999, Pages 508-513

Hill climbing in recurrent neural networks for learning the an/bsup n/cn language

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Indexed keywords

CONTEXT SENSITIVE LANGUAGES;

EID: 0002684367     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICONIP.1999.845646     Document Type: Conference Paper
Times cited : (9)

References (15)
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    • Casey, M. The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction, Neural Computation 8(6), 1135-1178, 1996.
    • (1996) Neural Computation , vol.8 , Issue.6 , pp. 1135-1178
    • Casey, M.1
  • 3
    • 26444565569 scopus 로고
    • Finding structure in time
    • Elman, J.L. Finding structure in time, Cognitive. Science 14, 179-211, 1990.
    • (1990) Cognitive. Science , vol.14 , pp. 179-211
    • Elman, J.L.1
  • 4
    • 0027636611 scopus 로고
    • Learning and development in neural networks: The importance of starting small
    • Elman, J.L. Learning and development in neural networks: The importance of starting small, Cognition 48, 71-99, 1993.
    • (1993) Cognition , vol.48 , pp. 71-99
    • Elman, J.L.1
  • 6
    • 0001327717 scopus 로고
    • Learning and extracting finite state automata with second-order recurrent neural networks
    • Giles, C.L., C.B. Miller, D. Chen, H.H. Chen, G.Z. Sun, Y.C. Lee. Learning and extracting finite state automata with second-order recurrent neural networks, Neural Computation 4(3), 393-405, 1992.
    • (1992) Neural Computation , vol.4 , Issue.3 , pp. 393-405
    • Giles, C.L.1    Miller, C.B.2    Chen, D.3    Chen, H.H.4    Sun, G.Z.5    Lee, Y.C.6
  • 9
    • 0001460434 scopus 로고
    • The induction of dynamical recognizers
    • Pollack, J. The induction of dynamical recognizers, Machine Learning 7, 227-252, 1991.
    • (1991) Machine Learning , vol.7 , pp. 227-252
    • Pollack, J.1
  • 10
    • 0033098329 scopus 로고    scopus 로고
    • A recurrent neural network that learns to count
    • Rodriguez, P., J. Wiles, J.L. Flman. A recurrent neural network that learns to count, Connection Science 11(1), 5-40, 1999.
    • (1999) Connection Science , vol.11 , Issue.1 , pp. 5-40
    • Rodriguez, P.1    Wiles, J.2    Flman, J.L.3
  • 11
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • Itumelhart, D.E., G.E. Hinton & R.J. Williams. Learning representations by back-propagating errors, Nature 323, 533-536, 1986.
    • (1986) Nature , vol.323 , pp. 533-536
    • Itumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 12
    • 0040509729 scopus 로고
    • Neural networks with real weights: Analog computational complexity
    • Siegelmann, H.T., E.D. Sontag. Neural networks with real weights: Analog computational complexity, Report SYCON-92-95, 1992.
    • (1992) Report SYCON-92-95
    • Siegelmann, H.T.1    Sontag, E.D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.