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Steven L. Brunton
Steven L. Brunton
Professor, University of Washington
Bestätigte E-Mail-Adresse bei uw.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
30882016
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
17622014
Machine learning for fluid mechanics
SL Brunton, BR Noack, P Koumoutsakos
Annual review of fluid mechanics 52, 477-508, 2020
17462020
Data-driven science and engineering: Machine learning, dynamical systems, and control
SL Brunton, JN Kutz
Cambridge University Press, 2019
14632019
Dynamic mode decomposition: data-driven modeling of complex systems
JN Kutz, SL Brunton, BW Brunton, JL Proctor
Society for Industrial and Applied Mathematics, 2016
13652016
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
13262017
Data-driven discovery of partial differential equations
SH Rudy, SL Brunton, JL Proctor, JN Kutz
Science advances 3 (4), e1602614, 2017
12062017
Deep learning for universal linear embeddings of nonlinear dynamics
B Lusch, JN Kutz, SL Brunton
Nature communications 9 (1), 4950, 2018
9372018
Dynamic mode decomposition with control
JL Proctor, SL Brunton, JN Kutz
SIAM Journal on Applied Dynamical Systems 15 (1), 142-161, 2016
8122016
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
5712019
Closed-loop turbulence control: Progress and challenges
SL Brunton, BR Noack
Applied Mechanics Reviews 67 (5), 050801, 2015
5262015
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
4692016
Chaos as an intermittently forced linear system
SL Brunton, BW Brunton, JL Proctor, E Kaiser, JN Kutz
Nature Communications 8 (19), 1--9, 2017
4632017
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
4462018
Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control
SL Brunton, CW Rowley, SR Kulkarni, C Clarkson
Power Electronics, IEEE Transactions on 25 (10), 2531-2540, 2010
4212010
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
3752020
Multiresolution dynamic mode decomposition
JN Kutz, X Fu, SL Brunton
SIAM Journal on Applied Dynamical Systems 15 (2), 713-735, 2016
3622016
Data-driven science and engineering: Machine learning, dynamical systems, and control
SL Brunton, JN Kutz
Cambridge University Press, 2022
3472022
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
3412016
Machine learning control-taming nonlinear dynamics and turbulence
T Duriez, SL Brunton, BR Noack
Springer International Publishing, 2017
3382017
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