Kutz JN - Search Results

1

Nonlinear control of networked dynamical systems.

Morrison M, Kutz JN. Morrison M, et al. Among authors: kutz jn. IEEE Trans Netw Sci Eng. 2021 Jan-Mar;8(1):174-189. doi: 10.1109/tnse.2020.3032117. Epub 2020 Oct 19. IEEE Trans Netw Sci Eng. 2021. PMID: 33997094 Free PMC article.

2

Nonlinear model reduction for dynamical systems using sparse sensor locations from learned libraries.

Sargsyan S, Brunton SL, Kutz JN. Sargsyan S, et al. Among authors: kutz jn. Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Sep;92(3):033304. doi: 10.1103/PhysRevE.92.033304. Epub 2015 Sep 10. Phys Rev E Stat Nonlin Soft Matter Phys. 2015. PMID: 26465583

3

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control.

Brunton SL, Brunton BW, Proctor JL, Kutz JN. Brunton SL, et al. Among authors: kutz jn. PLoS One. 2016 Feb 26;11(2):e0150171. doi: 10.1371/journal.pone.0150171. eCollection 2016. PLoS One. 2016. PMID: 26919740 Free PMC article.

4

Inferring connectivity in networked dynamical systems: Challenges using Granger causality.

Lusch B, Maia PD, Kutz JN. Lusch B, et al. Among authors: kutz jn. Phys Rev E. 2016 Sep;94(3-1):032220. doi: 10.1103/PhysRevE.94.032220. Epub 2016 Sep 27. Phys Rev E. 2016. PMID: 27739857

5

Model selection for dynamical systems via sparse regression and information criteria.

Mangan NM, Kutz JN, Brunton SL, Proctor JL. Mangan NM, et al. Among authors: kutz jn. Proc Math Phys Eng Sci. 2017 Aug;473(2204):20170009. doi: 10.1098/rspa.2017.0009. Epub 2017 Aug 30. Proc Math Phys Eng Sci. 2017. PMID: 28878554 Free PMC article.

6

Preventing Neurodegenerative Memory Loss in Hopfield Neuronal Networks Using Cerebral Organoids or External Microelectronics.

Morrison M, Maia PD, Kutz JN. Morrison M, et al. Among authors: kutz jn. Comput Math Methods Med. 2017;2017:6102494. doi: 10.1155/2017/6102494. Epub 2017 Sep 5. Comput Math Methods Med. 2017. PMID: 29312461 Free PMC article.

7

Sparse identification of nonlinear dynamics for model predictive control in the low-data limit.

Kaiser E, Kutz JN, Brunton SL. Kaiser E, et al. Among authors: kutz jn. Proc Math Phys Eng Sci. 2018 Nov;474(2219):20180335. doi: 10.1098/rspa.2018.0335. Epub 2018 Nov 14. Proc Math Phys Eng Sci. 2018. PMID: 30839858 Free PMC article.

8

Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems.

Li S, Kaiser E, Laima S, Li H, Brunton SL, Kutz JN. Li S, et al. Among authors: kutz jn. Phys Rev E. 2019 Aug;100(2-1):022220. doi: 10.1103/PhysRevE.100.022220. Phys Rev E. 2019. PMID: 31574688

9

Nonlinear Control in the Nematode C. elegans.

Morrison M, Fieseler C, Kutz JN. Morrison M, et al. Among authors: kutz jn. Front Comput Neurosci. 2021 Jan 22;14:616639. doi: 10.3389/fncom.2020.616639. eCollection 2020. Front Comput Neurosci. 2021. PMID: 33551783 Free PMC article.

10

Discovering governing equations from data by sparse identification of nonlinear dynamical systems.

Brunton SL, Proctor JL, Kutz JN. Brunton SL, et al. Among authors: kutz jn. Proc Natl Acad Sci U S A. 2016 Apr 12;113(15):3932-7. doi: 10.1073/pnas.1517384113. Epub 2016 Mar 28. Proc Natl Acad Sci U S A. 2016. PMID: 27035946 Free PMC article.

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