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Volumn , Issue , 2003, Pages

Adaptive nonlinear system identification with Echo State networks

Author keywords

[No Author keywords available]

Indexed keywords

RECURRENT NEURAL NETWORKS;

EID: 78349289898     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (305)

References (9)
  • 1
    • 0034186923 scopus 로고    scopus 로고
    • New results on recurrent network training: Unifying the algorithms and accelerating convergence
    • A.F. Atiya and A.G. Parlos. New results on recurrent network training: Unifying the algorithms and accelerating convergence. IEEE Trans. Neural Networks, 11(3): 697-709, 2000.
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.3 , pp. 697-709
    • Atiya, A.F.1    Parlos, A.G.2
  • 3
    • 0344592212 scopus 로고    scopus 로고
    • Enhanced multi-stream Kalman filter training for recurrent neural networks
    • J.A.K. Suykens and J. Vandewalle, editors Kluwer
    • L.A. Feldkamp, D.V. Prokhorov, C.F. Eagen, and F. Yuan. Enhanced multi-stream Kalman filter training for recurrent neural networks. In J.A.K. Suykens and J. Vandewalle, editors, Nonlinear Modeling: Advanced Black-Box Techniques, pages 29-54. Kluwer, 1998.
    • (1998) Nonlinear Modeling: Advanced Black-Box Techniques , pp. 29-54
    • Feldkamp, L.A.1    Prokhorov, D.V.2    Eagen, C.F.3    Yuan, F.4
  • 4
    • 10244240120 scopus 로고    scopus 로고
    • Learning to ground fact symbols in behavior-based robots
    • F. van Harmelen, editor IOS Press, Amsterdam
    • J. Hertzberg, H. Jaeger, and F. Schönherr. Learning to ground fact symbols in behavior-based robots. In F. van Harmelen, editor, Proc. 15th Europ. Conf. on Art. Int. (ECAI 02), pages 708-712. IOS Press, Amsterdam, 2002.
    • (2002) Proc. 15th Europ. Conf. on Art. Int. (ECAI 02) , pp. 708-712
    • Hertzberg, J.1    Jaeger, H.2    Schönherr, F.3
  • 7
    • 33749833931 scopus 로고    scopus 로고
    • Tutorial on training recurrent neural networks, covering BPPT, RTRL, EKF and the echo state network approach
    • H. Jaeger. Tutorial on training recurrent neural networks, covering BPPT, RTRL, EKF and the echo state network approach. GMD Report 159, Fraunhofer Institute AIS, 2002.
    • (2002) GMD Report 159, Fraunhofer Institute AIS
    • Jaeger, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.