Mostrar el registro sencillo del ítem
dc.contributor.author | Conejero, J. Alberto | es_ES |
dc.contributor.author | Lizama, C. | es_ES |
dc.contributor.author | Mira-Iglesias, Ainara | es_ES |
dc.contributor.author | Rodero-Gómez, Cristóbal | es_ES |
dc.date.accessioned | 2021-02-02T04:32:24Z | |
dc.date.available | 2021-02-02T04:32:24Z | |
dc.date.issued | 2019-10-03 | es_ES |
dc.identifier.issn | 1023-6198 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/160420 | |
dc.description.abstract | [EN] We study time series generated by the parametric family of fractional discrete maps introduced by Wu and Baleanu, presenting an alternative way of introducing these maps. For the values of the parameters that yield chaotic time series, we have studied the Shannon entropy of the degree distribution of the natural and horizontal visibility graphs associated to these series. In these cases, the degree distribution can be fitted with a power law. We have also compared the Shannon entropy and the exponent of the power law fitting for the different values of the fractionary exponent and the scaling factor of the model. Our results illustrate a connection between the fractionary exponent and the scaling factor of the maps, with the respect to the onset of the chaos. | es_ES |
dc.description.sponsorship | J.A. Conejero is supported Ministerio de Economia y Competitividad Grant Project MTM2016-75963-P. Carlos Lizama is supported by CONICYT, under Fondecyt Grant number 1180041. Cristobal Rodero-Gomez is funded by European Commission H2020 research and Innovation programme under the Marie Sklodowska-Curie grant agreement No. 764738. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Taylor & Francis | es_ES |
dc.relation.ispartof | The Journal of Difference Equations and Applications | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Discrete fractional calculus | es_ES |
dc.subject | Caputo delta difference | es_ES |
dc.subject | Logistic equation | es_ES |
dc.subject | Visibility graphs | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Visibility graphs of fractional Wu-Baleanu time series | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1080/10236198.2019.1619714 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/764738/EU/Personalised In-Silico Cardiology/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//MTM2016-75963-P/ES/DINAMICA DE OPERADORES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/CONICYT//1180041/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Conejero, JA.; Lizama, C.; Mira-Iglesias, A.; Rodero-Gómez, C. (2019). Visibility graphs of fractional Wu-Baleanu time series. The Journal of Difference Equations and Applications. 25(9-10):1321-1331. https://doi.org/10.1080/10236198.2019.1619714 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1080/10236198.2019.1619714 | es_ES |
dc.description.upvformatpinicio | 1321 | es_ES |
dc.description.upvformatpfin | 1331 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 25 | es_ES |
dc.description.issue | 9-10 | es_ES |
dc.relation.pasarela | S\392378 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.contributor.funder | Comisión Nacional de Investigación Científica y Tecnológica, Chile | es_ES |
dc.description.references | Anand, K., & Bianconi, G. (2009). Entropy measures for networks: Toward an information theory of complex topologies. Physical Review E, 80(4). doi:10.1103/physreve.80.045102 | es_ES |
dc.description.references | Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509 | es_ES |
dc.description.references | Brzeziński, D. W. (2017). Comparison of Fractional Order Derivatives Computational Accuracy - Right Hand vs Left Hand Definition. Applied Mathematics and Nonlinear Sciences, 2(1), 237-248. doi:10.21042/amns.2017.1.00020 | es_ES |
dc.description.references | Brzeziński, D. W. (2018). Review of numerical methods for NumILPT with computational accuracy assessment for fractional calculus. Applied Mathematics and Nonlinear Sciences, 3(2), 487-502. doi:10.2478/amns.2018.2.00038 | es_ES |
dc.description.references | DONNER, R. V., SMALL, M., DONGES, J. F., MARWAN, N., ZOU, Y., XIANG, R., & KURTHS, J. (2011). RECURRENCE-BASED TIME SERIES ANALYSIS BY MEANS OF COMPLEX NETWORK METHODS. International Journal of Bifurcation and Chaos, 21(04), 1019-1046. doi:10.1142/s0218127411029021 | es_ES |
dc.description.references | Edelman, M. (2015). On the fractional Eulerian numbers and equivalence of maps with long term power-law memory (integral Volterra equations of the second kind) to Grünvald-Letnikov fractional difference (differential) equations. Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(7), 073103. doi:10.1063/1.4922834 | es_ES |
dc.description.references | Edelman, M. (2018). On stability of fixed points and chaos in fractional systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(2), 023112. doi:10.1063/1.5016437 | es_ES |
dc.description.references | Gao, Z.-K., Small, M., & Kurths, J. (2016). Complex network analysis of time series. EPL (Europhysics Letters), 116(5), 50001. doi:10.1209/0295-5075/116/50001 | es_ES |
dc.description.references | Iacovacci, J., & Lacasa, L. (2016). Sequential visibility-graph motifs. Physical Review E, 93(4). doi:10.1103/physreve.93.042309 | es_ES |
dc.description.references | Indahl, U. G., Naes, T., & Liland, K. H. (2018). A similarity index for comparing coupled matrices. Journal of Chemometrics, 32(10), e3049. doi:10.1002/cem.3049 | es_ES |
dc.description.references | Kantz, H., & Schreiber, T. (2003). Nonlinear Time Series Analysis. doi:10.1017/cbo9780511755798 | es_ES |
dc.description.references | Lacasa, L., & Iacovacci, J. (2017). Visibility graphs of random scalar fields and spatial data. Physical Review E, 96(1). doi:10.1103/physreve.96.012318 | es_ES |
dc.description.references | Lacasa, L., Luque, B., Ballesteros, F., Luque, J., & Nuño, J. C. (2008). From time series to complex networks: The visibility graph. Proceedings of the National Academy of Sciences, 105(13), 4972-4975. doi:10.1073/pnas.0709247105 | es_ES |
dc.description.references | Lizama, C. (2015). lp-maximal regularity for fractional difference equations on UMD spaces. Mathematische Nachrichten, 288(17-18), 2079-2092. doi:10.1002/mana.201400326 | es_ES |
dc.description.references | Lizama, C. (2017). The Poisson distribution, abstract fractional difference equations, and stability. Proceedings of the American Mathematical Society, 145(9), 3809-3827. doi:10.1090/proc/12895 | es_ES |
dc.description.references | Luque, B., Lacasa, L., Ballesteros, F., & Luque, J. (2009). Horizontal visibility graphs: Exact results for random time series. Physical Review E, 80(4). doi:10.1103/physreve.80.046103 | es_ES |
dc.description.references | Luque, B., Lacasa, L., Ballesteros, F. J., & Robledo, A. (2011). Feigenbaum Graphs: A Complex Network Perspective of Chaos. PLoS ONE, 6(9), e22411. doi:10.1371/journal.pone.0022411 | es_ES |
dc.description.references | Luque, B., Lacasa, L., & Robledo, A. (2012). Feigenbaum graphs at the onset of chaos. Physics Letters A, 376(47-48), 3625-3629. doi:10.1016/j.physleta.2012.10.050 | es_ES |
dc.description.references | May, R. M. (1976). Simple mathematical models with very complicated dynamics. Nature, 261(5560), 459-467. doi:10.1038/261459a0 | es_ES |
dc.description.references | Núñez, Á. M., Luque, B., Lacasa, L., Gómez, J. P., & Robledo, A. (2013). Horizontal visibility graphs generated by type-I intermittency. Physical Review E, 87(5). doi:10.1103/physreve.87.052801 | es_ES |
dc.description.references | Ravetti, M. G., Carpi, L. C., Gonçalves, B. A., Frery, A. C., & Rosso, O. A. (2014). Distinguishing Noise from Chaos: Objective versus Subjective Criteria Using Horizontal Visibility Graph. PLoS ONE, 9(9), e108004. doi:10.1371/journal.pone.0108004 | es_ES |
dc.description.references | Robledo, A. (2013). Generalized Statistical Mechanics at the Onset of Chaos. Entropy, 15(12), 5178-5222. doi:10.3390/e15125178 | es_ES |
dc.description.references | Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379-423. doi:10.1002/j.1538-7305.1948.tb01338.x | es_ES |
dc.description.references | Song, C., Havlin, S., & Makse, H. A. (2006). Origins of fractality in the growth of complex networks. Nature Physics, 2(4), 275-281. doi:10.1038/nphys266 | es_ES |
dc.description.references | West, J., Lacasa, L., Severini, S., & Teschendorff, A. (2012). Approximate entropy of network parameters. Physical Review E, 85(4). doi:10.1103/physreve.85.046111 | es_ES |
dc.description.references | Wu, G.-C., & Baleanu, D. (2013). Discrete fractional logistic map and its chaos. Nonlinear Dynamics, 75(1-2), 283-287. doi:10.1007/s11071-013-1065-7 | es_ES |
dc.description.references | Wu, G.-C., & Baleanu, D. (2014). Discrete chaos in fractional delayed logistic maps. Nonlinear Dynamics, 80(4), 1697-1703. doi:10.1007/s11071-014-1250-3 | es_ES |
dc.description.references | Zhang, J., & Small, M. (2006). Complex Network from Pseudoperiodic Time Series: Topology versus Dynamics. Physical Review Letters, 96(23). doi:10.1103/physrevlett.96.238701 | es_ES |