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Volumn 20, Issue SUPPL.2, 1996, Pages

Self-consistency in neural network-based NLPC analysis with applications to time-series processing

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; IDENTIFICATION (CONTROL SYSTEMS); IMAGE PROCESSING; LINEAR CONTROL SYSTEMS; NONLINEAR CONTROL SYSTEMS; SELF ADJUSTING CONTROL SYSTEMS;

EID: 0029701817     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/0098-1354(96)00189-5     Document Type: Article
Times cited : (8)

References (17)
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  • 2
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    • Extracting qualitative dynamics from experimental data
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    • Broomhead, D.S.1    King, G.P.2
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    • Finding structure in time
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    • Elman, J.L.1
  • 6
    • 44049117992 scopus 로고
    • An analytic approach to practical state space reconstruction
    • Gibson, J. F., J. D. Farmer, M. Casdagli and S. Eubank, 1992, An analytic approach to practical state space reconstruction, Physica D, 57, 1-30.
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    • Gibson, J.F.1    Farmer, J.D.2    Casdagli, M.3    Eubank, S.4
  • 7
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    • Noise reduction: Finding the simplest dynamical system consistent with the data
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    • Kostelich, E.J.1    Yorke, J.A.2
  • 8
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    • Kramer, M.A.1
  • 10
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    • ODESSA - An ordinary differential equation solver with explicit simultaneous sensitivity analysis
    • Leis, J. R., and M. A. Kramer, 1988, ODESSA - an ordinary differential equation solver with explicit simultaneous sensitivity analysis, ACM Trans. Math. Software, 14, 61-67.
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    • Leis, J.R.1    Kramer, M.A.2
  • 11
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    • Principal components, minor components and linear neural networks
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    • Werbos, P.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.