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dc.contributor.authorde Jesus Euan Campos, Carolina
dc.contributor.authorSun, Ying
dc.contributor.authorOmbao, Hernando
dc.date.accessioned2017-12-28T07:32:11Z
dc.date.available2017-12-28T07:32:11Z
dc.date.issued2017-11-19
dc.identifier.urihttp://hdl.handle.net/10754/626473
dc.description.abstractWe develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by
dc.publisherarXiv
dc.relation.urlhttp://arxiv.org/abs/1711.07007v1
dc.relation.urlhttp://arxiv.org/pdf/1711.07007v1
dc.rightsArchived with thanks to arXiv
dc.titleCoherence-based Time Series Clustering for Brain Connectivity Visualization
dc.typePreprint
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.eprint.versionPre-print
dc.contributor.institutionDepartment of Statistics, University of California at Irvine (UCI), Irvine, CA 92697, USA
dc.identifier.arxividarXiv:1711.07007
kaust.personde Jesus Euan Campos, Carolina
kaust.personSun, Ying
kaust.personOmbao, Hernando
refterms.dateFOA2018-06-14T03:36:19Z


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