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  Observing spatio-temporal dynamics of excitable media using reservoir computing

Zimmermann, R. S., & Parlitz, U. (2018). Observing spatio-temporal dynamics of excitable media using reservoir computing. Chaos, 28(4): 043118. doi:10.1063/1.5022276.

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 Creators:
Zimmermann, Roland S.1, Author           
Parlitz, Ulrich1, Author           
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1Research Group Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063288              

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 Abstract: 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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Language(s): eng - English
 Dates: 2018-04-242018-04
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1063/1.5022276
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Title: Chaos
Source Genre: Journal
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Pages: 9 Volume / Issue: 28 (4) Sequence Number: 043118 Start / End Page: - Identifier: -