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Editorial

Special issue on ‘Applications of Continuous-Time Model Identification and Estimation’

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Miguel Aguiar, Amritam Das & Karl H. Johansson. (2023) Universal Approximation of Flows of Control Systems by Recurrent Neural Networks. Universal Approximation of Flows of Control Systems by Recurrent Neural Networks.
Marco Forgione & Dario Piga. (2021) Continuous-time system identification with neural networks: Model structures and fitting criteria. European Journal of Control 59, pages 69-81.
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Bojan Mavkov, Marco Forgione & Dario Piga. (2020) Integrated Neural Networks for Nonlinear Continuous-Time System Identification. IEEE Control Systems Letters, pages 1-1.
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Florian Reiterer, Hannes Gamper, Sandra Thaller, Patrick Schrangl, Helmut Kokal & Luigi del Re. (2018) Fast Parametrization of Vehicle Suspension Models. Fast Parametrization of Vehicle Suspension Models.
Sandra Thaller, Florian Reiterer, Roman Schmied, Harald Waschl, Helmut Kokal & Luigi del Re. (2016) Fast Determination of Vehicle Suspension Parameters via Continuous Time System Identification * *This work has been supported by the Linz Center of Mechatronics (LCM) in the framework of the Austrian COMET-K2 program.. IFAC-PapersOnLine 49:11, pages 448-453.
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M. Brunot, A. Janot, F. Carrillo, H. Garnier, P.O. Vandanjon & M. Gautier. (2015) Physical parameter identification of a one-degree-of-freedom electromechanical system operating in closed loop. IFAC-PapersOnLine 48:28, pages 823-828.
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