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Detection of generalized synchronization using echo state networks

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dc.contributor.author Ibáñez-Soria, D.
dc.contributor.author García Ojalvo, Jordi
dc.contributor.author Soria Frisch, Aureli
dc.contributor.author Ruffini, G.
dc.date.accessioned 2018-05-04T07:43:05Z
dc.date.issued 2018
dc.identifier.citation Ibáñez-Soria D, Garcia-Ojalvo J, Soria-Frisch A, Ruffini G. Detection of generalized synchronization using echo state networks. Chaos 2018 Mar; 28(3): 033118. DOI: 10.1063/1.5010285
dc.identifier.issn 1054-1500
dc.identifier.uri http://hdl.handle.net/10230/34556
dc.description.abstract Generalized synchronization between coupled dynamical systems is a phenomenon of relevance in applications that range from secure communications to physiological modelling. Here, we test the capabilities of reservoir computing and, in particular, echo state networks for the detection of generalized synchronization. A nonlinear dynamical system consisting of two coupled Rössler chaotic attractors is used to generate temporal series consisting of time-locked generalized synchronized sequences interleaved with unsynchronized ones. Correctly tuned, echo state networks are able to efficiently discriminate between unsynchronized and synchronized sequences even in the presence of relatively high levels of noise. Compared to other state-of-the-art techniques of synchronization detection, the online capabilities of the proposed Echo State Network based methodology make it a promising choice for real-time applications aiming to monitor dynamical synchronization changes in continuous signals.
dc.description.sponsorship We would like to thank the European Union's Horizon 2020 research and innovation programme who has partially funded the work of David Ibáñez and Aureli Soria-Frisch through the STIPED project under Grant Agreement No. 731827. We would also like to thank the support from ICREA Academia program and the Spanish Ministry of Economy and Competitiveness and FEDER (Project FIS2015-66503-C3-1-P and Maria de Maeztu Programme for Units of Excellence in R&D, MDM-2014-0370).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher American Institute of Physics (AIP)
dc.relation.ispartof Chaos 2018 Mar; 28(3): 033118
dc.rights © American Institute of Physics. The following article appeared in Ibáñez-Soria et al., Chaos. 28, 2018 and may be found at https://doi.org/10.1063/1.5010285
dc.title Detection of generalized synchronization using echo state networks
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1063/1.5010285
dc.subject.keyword Reservoir computing
dc.subject.keyword Generalized synchronization
dc.subject.keyword Echo state networks
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/731827
dc.rights.accessRights info:eu-repo/semantics/embargoedAccess
dc.type.version info:eu-repo/semantics/publishedVersion
dc.embargo.liftdate 2019-03-01
dc.date.embargoEnd info:eu-repo/date/embargoEnd/2019-03-01

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