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Neural network modules conditioned by known priors can be effectively trained and combined to represent systems with nonlinear dynamics.
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Roger W. Brockett · 1976
Earlier work this paper cites.
Non-linear system identification using neural networks
S. Chen, S. A. Billings, and P. M. Grant · 1990
Earlier work this paper cites.
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Byung-Jae Kwak, A. E. Yagle, and J. A. Levitt · 1998
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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N. Chiras, C. Evans, and D. Rees · 2001
Earlier work this paper cites.
Nonlinear systems; 3rd ed
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Earlier work this paper cites.
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Earlier work this paper cites.
Identification of hammerstein models with cubic spline nonlinearities
E. J. Dempsey and D. T. Westwick · 2004
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Jeen-Shing Wang and Yi-Chung Chen · 2008
Earlier work this paper cites.
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Robert Wilson and Leif Finkel · 2009
Earlier work this paper cites.
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Later among the works it cites.
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Later among the works it cites.
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https://www.mathworks.com/help/ident/ug/modeling-an-aerodynamic-body.html
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