A Comparative Study of Dynamic Mode Decomposition (DMD) and Dynamical Component Analysis (DyCA)
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-58653-9_9
Reference12 articles.
1. Brunton, B.W., Johnson, L.A., Ojemann, J.G., Kutz, J.N.: Extracting spatial-temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition. J. Neurosci. Methods 258, 1–15 (2015)
2. Chen, K.K., Tu, J.H., Rowley, C.W.: Variants of dynamic mode decomposition: boundary condition. Koopman and Fourier analyses. J. Nonlinear Sci. 22, 887–915 (2012)
3. Jovanović, M.R., Schmid, P.J., Nichols, J.W.: Sparsity-promoting dynamic mode decomposition. Phys. Fluids 26, 024103 (2014)
4. Korn, K., Seifert, B., Uhl, C.: Dynamical Component Analysis (DyCA) and its application on epileptic EEG. In: ICASSP, pp. 1100–1104. IEEE (2019)
5. Kutz, J.N., Fu, X., Brunton, S.L.: Multiresolution dynamic mode decomposition. SIAM J. Appl. Dyn. Syst. 15, 713–735 (2016)
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