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dc.contributor.author | Leguia, Marc G. |
dc.contributor.author | Martínez, Cristina G. B. |
dc.contributor.author | Malvestio, Irene |
dc.contributor.author | Tauste Campo, Adrià |
dc.contributor.author | Rocamora, Rodrigo |
dc.contributor.author | Levnajić, Zoran |
dc.contributor.author | Andrzejak, Ralph Gregor |
dc.date.accessioned | 2019-11-06T12:08:03Z |
dc.date.available | 2019-11-06T12:08:03Z |
dc.date.issued | 2019 |
dc.identifier.citation | Leguia MG, Martínez CGB, Malvestio I, Tauste Campo A, Rocamora R, Levnajić Z, Andrzejak RG. Inferring directed networks using a rank-based connectivity measure [software]. Repositori Digital de la UPF: Barcelona; 2019. Available from: http://hdl.handle.net/10230/42764 |
dc.identifier.uri | http://hdl.handle.net/10230/42764 |
dc.description | MATLAB source codes (.m) and README (.pdf) |
dc.description.abstract | This page provides the source code underlying the manuscript: Leguia MG, Martínez CGB, Malvestio I, Campo A T, Rocamora R, Levnajic Z, Andrzejak RG. 2019. Inferring directed networks using a rank-based connectivity measure. Phys. Rev. E. 99, 012319 If you use any of these resources, please make sure that you cite this reference. For more detailed information, please refer to https://www.upf.edu/web/ntsa/downloads |
dc.description.sponsorship | This work was funded by the EU via H2020 Marie Sklodowska-Curie project COSMOS, Grant No. 642563 (M.G.L., I.M., Z.L., and R.G.A). R.G.A. and C.G.B.M. acknowledge funding from the Spanish Ministry of Economy and Competitiveness (Grant No. FIS2014-54177-R) and the CERCA Programme/Generalitat de Catalunya. C.G.B.M. acknowledges the support by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (Grant No. MDM-2015-0502). |
dc.format.mimetype | application/pdf |
dc.language.iso | eng |
dc.publisher | Universitat Pompeu Fabra |
dc.relation | Publicació relacionada: Leguia MG, Martínez CGB, Malvestio I, Tauste Campo A, Rocamora R, Levnajić Z, Andrzejak RG. Inferring directed networks using a rank-based connectivity measure. Phys Rev E.2019 Jan 22;99(1):012319. DOI: 10.1103/PhysRevE.99.012319 http://hdl.handle.net/10230/41825 |
dc.relation.isreferencedby | http://hdl.handle.net/10230/41825 |
dc.rights | Licensed under a Creative Commons License (CC-BY) 4.0 |
dc.rights | The source codes, data and results on these sites are free of charge for research and education purposes only. Any commercial or military use is prohibited. All resources are provided without any expressed or implied warranty. In no event the authors of the article or any of their host institutions are liable for any damages arising from the use of the software, data or results. |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ |
dc.subject.other | Chaotic systems |
dc.subject.other | Collective dynamics |
dc.subject.other | Directed networks |
dc.subject.other | Electroencephalography |
dc.subject.other | Nonlinear dynamics |
dc.subject.other | Networks |
dc.title | Inferring directed networks using a rank-based connectivity measure [software] |
dc.type | info:eu-repo/semantics/other |
dc.type | Software |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/642563 |
dc.relation.projectID | info:eu-repo/grantAgreement/ES/1PE/FIS2014-54177-R |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |