Volume 13
Issue 7
IEEE/CAA Journal of Automatica Sinica
| Citation: | Z. Yuan, J. Ding, D. Shen, and M. Xiao, “Random search deep neural networks driven Koopman subspace modeling of nonlinear dynamics,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 7, pp. 1770–1772, Jul. 2026. doi: 10.1109/JAS.2025.125612 |
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P. Bevanda, S. Sosnowski, and S. Hirche, “Koopman operator dynamical models: Learning, analysis and control,” Annual Reviews in Control, vol. 52, pp. 197–212, 2021. doi: 10.1016/j.arcontrol.2021.09.002
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H. Eivazi, L. Guastoni, P. Schlatter, H. Azizpour, and R. Vinuesa, “Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence,” Int. J. Heat and Fluid Flow, vol. 90, Art. no. 108816, 2021. doi: 10.1016/j.ijheatfluidflow.2021.108816
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