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Memory order decomposition of symbolic sequences

dc.contributor.authorAlvarez-Rodriguez, U.
dc.contributor.authorLatora, V.
dc.date.accessioned2023-08-29T11:36:36Z
dc.date.available2023-08-29T11:36:36Z
dc.date.issued2021-07-01
dc.identifier.citationPhysical Review E: 104 (1): 14112 (2021)es_ES
dc.identifier.urihttp://hdl.handle.net/10810/62267
dc.description.abstractWe introduce a general method for the study of memory in symbolic sequences based on higher-order Markov analysis. The Markov process that best represents a sequence is expressed as a mixture of matrices of minimal orders, enabling the definition of the so-called memory profile, which unambiguously reflects the true order of correlations. The method is validated by recovering the memory profiles of tunable synthetic sequences. Finally, we scan real data and showcase with practical examples how our protocol can be used to extract relevant stochastic properties of symbolic sequences. © 2021 American Physical Society.es_ES
dc.description.sponsorshipU.A.-R. acknowledges support from the Spanish Government through Maria de Maeztu excellence accreditation 2018-2022 (Ref. No. MDM-2017-0714), from the Basque Government through the Posdoctoral Program (Ref. No. POS-2017-1-0022) and from the Swiss National Science Foundation (Ref. No. 176938). V.L. acknowledges support from the EPSRC Project No. EP/N013492/1 and from the Leverhulme Trust Research Fellowship “CREATE: The network components of creativity and success.”es_ES
dc.language.isoenges_ES
dc.publisherPhysical Review Ees_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.subjectGeneral methodes_ES
dc.subjectHigher-orderes_ES
dc.subjectMarkov analysises_ES
dc.subjectMemory orderinges_ES
dc.subjectProtocol canses_ES
dc.subjectStochastic propertieses_ES
dc.subjectSymbolic sequencees_ES
dc.subjectSynthetic sequencees_ES
dc.titleMemory order decomposition of symbolic sequenceses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2021 American Physical Society.es_ES
dc.rights.holderAtribución-NoComercial-CompartirIgual 3.0 España*
dc.relation.publisherversionhttps://dx.doi.org/10.1103/PhysRevE.104.014112es_ES
dc.identifier.doi10.1103/PhysRevE.104.014112
dc.contributor.funderEPSRC
dc.contributor.funderLeverhulme Trust
dc.contributor.funderSwiss National Science Foundation
dc.contributor.funderBasque Government


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© 2021 American Physical Society.
Except where otherwise noted, this item's license is described as © 2021 American Physical Society.