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dc.contributor.authorMiniussi, Myriam-
dc.contributor.authorOtt, Thomas-
dc.contributor.authorFellermann, Harold-
dc.date.accessioned2020-11-19T10:44:05Z-
dc.date.available2020-11-19T10:44:05Z-
dc.date.issued2020-11-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/20863-
dc.description.abstractStudies of network dynamics are typically concerned either with the evolution of network topologies or with the dynamics of nodes in networks with static connectivity. Yet, in many important real-world systems, the interplay between network evolution and node dynamics gives rise to versatile behavior such as adaptive learning in neural systems or opinion dynamics in social systems. Here, we expand on previous work by Ott et al. [1] on synchronization of coupled maps with adaptive network connectivity. We investigate the dynamic regimes of this model by analyzing common network topology measures (shortest path, clustering coefficient, and node betweenness). We further evaluate the impact of network size on the observed dynamic behavior. Finally, we quantify the effect of additive noise on the system's ability to synchronize. We find node betweenness to capture some of the features obtained by node inequality and mutual information, while shortest path and clustering coefficient does not. Furthermore, our current investigations suggest that increasing network size limits the range of responses we can obtain from the model, and in some cases, severely impacts node synchronization. Additive noise, on the other hand, leads to an increase in glassy relaxation dynamics that enable the system to overcome metastable states. More work is needed to properly understand the complex dynamics arising from the model. Finally, we offer some input as to how this model could be useful to understand opinion formation in social environments.de_CH
dc.language.isoende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectCoupled networksde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleImpact of noise and network size in coupled maps with asymmetric influence amplificationde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
zhaw.conference.details2020 International Symposium on Nonlinear Theory and Its Applications (NOLTA2020), Online Conference, 16-19 November 2020de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end285de_CH
zhaw.pages.start282de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsProceedings of the NOLTA 2020 Conferencede_CH
zhaw.webfeedBio-Inspired Methods & Neuromorphic Computingde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen Life Sciences und Facility Management

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Miniussi, M., Ott, T., & Fellermann, H. (2020). Impact of noise and network size in coupled maps with asymmetric influence amplification [Conference paper]. Proceedings of the NOLTA 2020 Conference, 282–285.
Miniussi, M., Ott, T. and Fellermann, H. (2020) ‘Impact of noise and network size in coupled maps with asymmetric influence amplification’, in Proceedings of the NOLTA 2020 Conference, pp. 282–285.
M. Miniussi, T. Ott, and H. Fellermann, “Impact of noise and network size in coupled maps with asymmetric influence amplification,” in Proceedings of the NOLTA 2020 Conference, Nov. 2020, pp. 282–285.
MINIUSSI, Myriam, Thomas OTT und Harold FELLERMANN, 2020. Impact of noise and network size in coupled maps with asymmetric influence amplification. In: Proceedings of the NOLTA 2020 Conference. Conference paper. November 2020. S. 282–285
Miniussi, Myriam, Thomas Ott, and Harold Fellermann. 2020. “Impact of Noise and Network Size in Coupled Maps with Asymmetric Influence Amplification.” Conference paper. In Proceedings of the NOLTA 2020 Conference, 282–85.
Miniussi, Myriam, et al. “Impact of Noise and Network Size in Coupled Maps with Asymmetric Influence Amplification.” Proceedings of the NOLTA 2020 Conference, 2020, pp. 282–85.


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