Mostra el registre d'ítem simple
Inferring the connectivity of coupled chaotic oscillators using Kalman filtering
dc.contributor.author | Forero Ortiz, Edwar Andres |
dc.contributor.author | Tirabassi, Giulio |
dc.contributor.author | Masoller Alonso, Cristina |
dc.contributor.author | Pons Rivero, Antonio Javier |
dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Enginyeria Civil |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Física |
dc.date.accessioned | 2022-05-16T13:52:13Z |
dc.date.available | 2022-05-16T13:52:13Z |
dc.date.issued | 2021-11-17 |
dc.identifier.citation | Forero, E. [et al.]. Inferring the connectivity of coupled chaotic oscillators using Kalman filtering. "Scientific reports", 17 Novembre 2021, vol. 11, p. 22376:1-22376:11. |
dc.identifier.issn | 2045-2322 |
dc.identifier.uri | http://hdl.handle.net/2117/367391 |
dc.description.abstract | Inferring the interactions between coupled oscillators is a significant open problem in complexity science, with multiple interdisciplinary applications. While the Kalman filter (KF) technique is a well-known tool, widely used for data assimilation and parameter estimation, to the best of our knowledge, it has not yet been used for inferring the connectivity of coupled chaotic oscillators. Here we demonstrate that KF allows reconstructing the interaction topology and the coupling strength of a network of mutually coupled Rössler-like chaotic oscillators. We show that the connectivity can be inferred by considering only the observed dynamics of a single variable of the three that define the phase space of each oscillator. We also show that both the coupling strength and the network architecture can be inferred even when the oscillators are close to synchronization. Simulation results are provided to show the effectiveness and applicability of the proposed method. |
dc.description.sponsorship | This work was supported in part by Spanish Ministerio de Ciencia, Innovación y Universidades (PGC2018- 099443-B-I00), AGAUR FI scholarship (E.F.) and ICREA ACADEMIA (C. M.), Generalitat de Catalunya. |
dc.language.iso | eng |
dc.publisher | Nature |
dc.rights | Attribution 4.0 |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ |
dc.subject | Àrees temàtiques de la UPC::Física |
dc.subject.lcsh | Nonlinear oscillations |
dc.subject.lcsh | Kalman filtering |
dc.title | Inferring the connectivity of coupled chaotic oscillators using Kalman filtering |
dc.type | Article |
dc.subject.lemac | Oscil·lacions no lineals |
dc.subject.lemac | Kalman, Filtratge de |
dc.contributor.group | Universitat Politècnica de Catalunya. DONLL - Dinàmica no Lineal, Òptica no Lineal i Làsers |
dc.identifier.doi | 10.1038/s41598-021-01444-7 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://www.nature.com/articles/s41598-021-01444-7 |
dc.rights.access | Open Access |
local.identifier.drac | 32226016 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-099443-B-I00/ES/SISTEMAS DINAMICOS COMPLEJOS Y HERRAMIENTAS AVANZADAS DE ANALISIS DE DATOS/ |
local.citation.author | Forero, E.; Tirabassi, G.; Masoller, C.; Pons, A. J. |
local.citation.publicationName | Scientific reports |
local.citation.volume | 11 |
local.citation.startingPage | 22376:1 |
local.citation.endingPage | 22376:11 |
Fitxers d'aquest items
Aquest ítem apareix a les col·leccions següents
-
Articles de revista [341]
-
Articles de revista [2.208]
-
Articles de revista [166]