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dc.contributor.advisorShi, Jianjun
dc.contributor.advisorMei, Yajun
dc.contributor.authorNabhan, Mohammad Abubaker
dc.date.accessioned2020-09-08T12:38:46Z
dc.date.available2020-09-08T12:38:46Z
dc.date.created2019-08
dc.date.issued2019-05-01
dc.date.submittedAugust 2019
dc.identifier.urihttp://hdl.handle.net/1853/63495
dc.description.abstractThis thesis contributes to the area of System Informatics and Control (SIAC) to develop systematic and dynamic methodologies for effective monitoring and change detection in complex systems. We propose sampling method named “Correlation based Dynamic Sampling” (CDS). It leverages spatial dependencies within data streams to improve decision making, when deploying sensors with resource limitations. Furthermore, we develop a dimension reduction method named “Robust Sparse Principal Component Analysis” (RS-PCA), that is designed to robustly estimate a lower dimensional subspace by exploiting sparse data structures. The probabilistic approach for modelling offers a direct medium for making inferences on system conditions. Additionally, we extends the aforementioned RS-PCA procedure for implementation in dynamic systems. The proposed adaptive RS-PCA method reduces the false alarm rate that may result from implementing static procedures. These strategies are implemented on several exemplary systems to assess their capability for real time application in practical scenarios.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectAdaptive
dc.subjectPartial observations
dc.subjectLimited resources
dc.subjectData fusion
dc.subjectSpatial structure
dc.subjectPrincipal component analysis
dc.subjectDimension reduction
dc.titleDynamic robust sparse modeling and sampling of high-dimensional data streams for online monitoring and change detection
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentIndustrial and Systems Engineering
thesis.degree.levelDoctoral
dc.contributor.committeeMemberGebraeel, Nagi
dc.contributor.committeeMemberPaynabar, Kamran
dc.contributor.committeeMemberLiu, Kaibo
dc.date.updated2020-09-08T12:38:46Z


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