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Steven L. Brunton
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Zitiert von
Zitiert von
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Discovering governing equations from data by sparse identification of nonlinear dynamical systems
SL Brunton, JL Proctor, JN Kutz
Proceedings of the national academy of sciences 113 (15), 3932-3937, 2016
49512016
Data-driven science and engineering: Machine learning, dynamical systems, and control
SL Brunton, JN Kutz
Cambridge University Press, 2022
31732022
Machine learning for fluid mechanics
SL Brunton, BR Noack, P Koumoutsakos
Annual review of fluid mechanics 52 (1), 477-508, 2020
28082020
On dynamic mode decomposition: Theory and applications
JH Tu, CW Rowley, DM Luchtenburg, SL Brunton, JN Kutz
Journal of Computational Dynamics 1 (2), 391-421, 2014
23552014
Dynamic mode decomposition: data-driven modeling of complex systems
JN Kutz, SL Brunton, BW Brunton, JL Proctor
Society for Industrial and Applied Mathematics, 2016
19892016
Modal analysis of fluid flows: An overview
K Taira, SL Brunton, STM Dawson, CW Rowley, T Colonius, BJ McKeon, ...
AIAA journal 55 (12), 4013-4041, 2017
19042017
Data-driven discovery of partial differential equations
SH Rudy, SL Brunton, JL Proctor, JN Kutz
Science advances 3 (4), e1602614, 2017
17092017
Deep learning for universal linear embeddings of nonlinear dynamics
B Lusch, JN Kutz, SL Brunton
Nature communications 9 (1), 4950, 2018
14792018
Dynamic mode decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142-161, 2016
12072016
Data-driven discovery of coordinates and governing equations
K Champion, B Lusch, JN Kutz, SL Brunton
Proceedings of the National Academy of Sciences 116 (45), 22445-22451, 2019
9652019
Sparse identification of nonlinear dynamics for model predictive control in the low-data limit
E Kaiser, JN Kutz, SL Brunton
Proceedings of the Royal Society A 474 (2219), 20180335, 2018
7212018
Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control
SL Brunton, BW Brunton, JL Proctor, JN Kutz
PloS one 11 (2), e0150171, 2016
6732016
Closed-loop turbulence control: Progress and challenges
SL Brunton, BR Noack
Applied Mechanics Reviews 67 (5), 050801, 2015
6662015
Chaos as an intermittently forced linear system
SL Brunton, BW Brunton, JL Proctor, E Kaiser, JN Kutz
Nature Communications 8 (19), 1--9, 2017
6522017
Modal analysis of fluid flows: Applications and outlook
K Taira, MS Hemati, SL Brunton, Y Sun, K Duraisamy, S Bagheri, ...
AIAA journal 58 (3), 998-1022, 2020
5672020
Modern Koopman theory for dynamical systems
SL Brunton, M Budišić, E Kaiser, JN Kutz
arXiv preprint arXiv:2102.12086, 2021
5632021
Data-driven sparse sensor placement for reconstruction: Demonstrating the benefits of exploiting known patterns
K Manohar, BW Brunton, JN Kutz, SL Brunton
IEEE Control Systems Magazine 38 (3), 63-86, 2018
4942018
Inferring biological networks by sparse identification of nonlinear dynamics
NM Mangan, SL Brunton, JL Proctor, JN Kutz
IEEE Transactions on Molecular, Biological, and Multi-Scale Communications 2 …, 2016
4912016
Multiresolution dynamic mode decomposition
JN Kutz, X Fu, SL Brunton
SIAM Journal on Applied Dynamical Systems 15 (2), 713-735, 2016
4682016
Machine learning control-taming nonlinear dynamics and turbulence
T Duriez, SL Brunton, BR Noack
Springer International Publishing, 2017
4422017
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