Observing spatio-temporal dynamics of excitable media using reservoir computing
We present a dynamical observer for two dimensional partial differential equation models describing excitable media, where the required cross prediction from observed time series to not measured state variables is provided by Echo State Networks receiving input from local regions in space, only. The...
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Veröffentlicht in: | Chaos (Woodbury, N.Y.) N.Y.), 2018-04, Vol.28 (4), p.043118-043118 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | We present a dynamical observer for two dimensional partial differential equation models describing excitable media, where the required cross prediction from observed time series to not measured state variables is provided by Echo State Networks receiving input from local regions in space, only. The efficacy of this approach is demonstrated for (noisy) data from a (cubic) Barkley model and the Bueno-Orovio-Cherry-Fenton model describing chaotic electrical wave propagation in cardiac tissue. |
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ISSN: | 1054-1500 1089-7682 |
DOI: | 10.1063/1.5022276 |