메뉴 건너뛰기




Volumn 34, Issue 3, 1998, Pages 151-158

A learning result for continuous-time recurrent neural networks

Author keywords

Computational learning theory; Recurrent neural networks; System identification

Indexed keywords


EID: 0012596163     PISSN: 01676911     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-6911(98)00006-1     Document Type: Article
Times cited : (22)

References (22)
  • 1
    • 0027795346 scopus 로고
    • For neural networks, function determines form
    • F. Albertini, E.D. Sontag, For neural networks, function determines form, Neural Networks 6 (1993) 975-990.
    • (1993) Neural Networks , vol.6 , pp. 975-990
    • Albertini, F.1    Sontag, E.D.2
  • 2
    • 0028417030 scopus 로고
    • State observability in recurrent neural networks
    • F. Albertini, E.D. Sontag, State observability in recurrent neural networks, Systems Control Lett. 22 (1994) 235-244.
    • (1994) Systems Control Lett. , vol.22 , pp. 235-244
    • Albertini, F.1    Sontag, E.D.2
  • 3
    • 0000029787 scopus 로고
    • FIR and UR synapses, a new neural network architecture for time-series modeling
    • A.D. Back, A.C. Tsoi, FIR and UR synapses, a new neural network architecture for time-series modeling, Neural Comput. 3 (1991) 375-385.
    • (1991) Neural Comput. , vol.3 , pp. 375-385
    • Back, A.D.1    Tsoi, A.C.2
  • 6
    • 0030241029 scopus 로고    scopus 로고
    • Sample complexity for learning recurrent perceptron mappings
    • B. Dasgupta, E.D. Sontag, Sample complexity for learning recurrent perceptron mappings, IEEE Trans. Inform. Theory 42 (1996) 1479-1487.
    • (1996) IEEE Trans. Inform. Theory , vol.42 , pp. 1479-1487
    • Dasgupta, B.1    Sontag, E.D.2
  • 7
    • 0029256399 scopus 로고
    • Bounding the Vapnik-Chervonenkis dimension of concept classes parametrized by real numbers
    • P. Goldberg, M. Jerrum, Bounding the Vapnik-Chervonenkis dimension of concept classes parametrized by real numbers, Machine Learning 18 (1995) 131-148.
    • (1995) Machine Learning , vol.18 , pp. 131-148
    • Goldberg, P.1    Jerrum, M.2
  • 8
    • 0002192516 scopus 로고
    • Decision theoretic generalizations of the PAC model for neural nets and other learning applications
    • D. Haussler, Decision theoretic generalizations of the PAC model for neural nets and other learning applications, Inform. Comput. 100 (1992) 78-150.
    • (1992) Inform. Comput. , vol.100 , pp. 78-150
    • Haussler, D.1
  • 9
    • 84949301057 scopus 로고    scopus 로고
    • Polynomial bounds for VC dimension of sigmoidal and general Pfaffian neural networks
    • to appear
    • M. Karpinski, A. Macintyre, Polynomial bounds for VC dimension of sigmoidal and general Pfaffian neural networks, J. Comput. System Sci., to appear. (Summary in: Polynomial bounds for VC dimension of sigmoidal neural networks, in: Proc. 27th ACM Symp. on Theory of Computing, 1995, pp. 200-208.)
    • J. Comput. System Sci.
    • Karpinski, M.1    Macintyre, A.2
  • 10
    • 0001788040 scopus 로고
    • Polynomial bounds for VC dimension of sigmoidal neural networks
    • M. Karpinski, A. Macintyre, Polynomial bounds for VC dimension of sigmoidal and general Pfaffian neural networks, J. Comput. System Sci., to appear. (Summary in: Polynomial bounds for VC dimension of sigmoidal neural networks, in: Proc. 27th ACM Symp. on Theory of Computing, 1995, pp. 200-208.)
    • (1995) Proc. 27th ACM Symp. on Theory of Computing , pp. 200-208
  • 14
    • 0002663413 scopus 로고
    • Turing computability with neural nets
    • H.T. Siegelmann, E.D. Sontag, Turing computability with neural nets, Appl. Math. Lett. 4 (6) (1991) 77-80.
    • (1991) Appl. Math. Lett. , vol.4 , Issue.6 , pp. 77-80
    • Siegelmann, H.T.1    Sontag, E.D.2
  • 17
    • 0009038890 scopus 로고    scopus 로고
    • Recurrent neural networks: Some systems-theoretic aspects
    • M. Karny, K. Warwick, V. Kurkova (Eds.), Springer, London, to appear
    • E.D. Sontag, Recurrent neural networks: some systems-theoretic aspects, in: M. Karny, K. Warwick, V. Kurkova (Eds.), Dealing with Complexity: a Neural Network Approach, Springer, London, 1998, to appear.
    • (1998) Dealing with Complexity: A Neural Network Approach
    • Sontag, E.D.1
  • 18
    • 0031146078 scopus 로고    scopus 로고
    • Complete controllability of continuous-time recurrent neural networks
    • E.D. Sontag, H.J. Sussmann, Complete controllability of continuous-time recurrent neural networks, Systems Control Lett. 30 (4) (1997) 177-183.
    • (1997) Systems Control Lett. , vol.30 , Issue.4 , pp. 177-183
    • Sontag, E.D.1    Sussmann, H.J.2
  • 21
    • 0027335110 scopus 로고
    • Lie algebra of recurrent neural networks and identifiability
    • San Francisco
    • R. Zbikowski, Lie algebra of recurrent neural networks and identifiability, in: Proc. Amer. Automatic Control Conference, San Francisco, 1993, pp. 2900-2901.
    • (1993) Proc. Amer. Automatic Control Conference , pp. 2900-2901
    • Zbikowski, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.