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Volumn 5, Issue , 1998, Pages 2874-2878

Neural state estimators for direct model-based fault diagnosis

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION PROBLEM; FINITE MEMORY; MODEL-BASED FAULT DIAGNOSIS; NEURAL ESTIMATION; NEURAL STATE; NEURAL WEIGHTS; OPTIMAL FUNCTION; STOCHASTIC APPROXIMATION ALGORITHMS;

EID: 23944486268     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACC.1998.688382     Document Type: Conference Paper
Times cited : (7)

References (12)
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  • 2
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  • 3
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  • 4
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    • Robust nonlinear fault diagnosis in input-output systems
    • A. T. Vemuri and M. Polycarpou, "Robust nonlinear fault diagnosis in input-output systems,", Int. J. of Control, Vol. 68, no. 2, pp. 343-360, 1997.
    • (1997) Int. J. of Control , vol.68 , Issue.2 , pp. 343-360
    • Vemuri, A.T.1    Polycarpou, M.2
  • 5
    • 0030692539 scopus 로고    scopus 로고
    • Model-based fault diagnosis using nonlinear estimators: A neural approach
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  • 6
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    • Fault detection and diagnosis in propulsion systems: A fault parameter estimation approach
    • A. Duyar, V. Eldem, W. Merril, and T. Guo, "Fault detection and diagnosis in propulsion systems: A fault parameter estimation approach,", Journal of Guidance, Control, and Dynamics, Vol. 17, no. 1, pp. 104-108, 1994.
    • (1994) Journal of Guidance, Control, and Dynamics , vol.17 , Issue.1 , pp. 104-108
    • Duyar, A.1    Eldem, V.2    Merril, W.3    Guo, T.4
  • 8
    • 0031141599 scopus 로고    scopus 로고
    • Neural approximators for nonlinear finite-memory state estimation
    • A. Alessandri, T. Parisini, and R. Zoppoli, "Neural approximators for nonlinear finite-memory state estimation,", Int. J. of Control, Vol. 67, no. 2, pp. 275-302, 1997.
    • (1997) Int. J. of Control , vol.67 , Issue.2 , pp. 275-302
    • Alessandri, A.1    Parisini, T.2    Zoppoli, R.3
  • 9
    • 0027599793 scopus 로고
    • Universal approximation bounds for superpositions of a sigmoidal function
    • A. R. Barron, "Universal approximation bounds for superpositions of a sigmoidal function,", IEEE Trans. on Information Theory, Vol. 39, pp. 930-945, 1993.
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  • 10
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  • 11
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    • Back-propagation trough adjoints for the identification of nonlinear dynamic systems using recurrent neural models
    • B. Srinivasan, U. R. Prasad, and N. J. Rao, "Back-propagation trough adjoints for the identification of nonlinear dynamic systems using recurrent neural models,", IEEE Trans, on Neural Networks, Vol. 5, no. 2, pp. 213-228, 1994.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.