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Distributed Hybrid Power State Estimation Under PMU Sampling Phase Errors

Author(s): Du, Jian; Ma, Shaodan; Wu, Yik-Chung; Poor, H Vincent

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dc.contributor.authorDu, Jian-
dc.contributor.authorMa, Shaodan-
dc.contributor.authorWu, Yik-Chung-
dc.contributor.authorPoor, H Vincent-
dc.date.accessioned2024-01-11T15:22:32Z-
dc.date.available2024-01-11T15:22:32Z-
dc.date.issued2014-11-13en_US
dc.identifier.citationDu, Jian, Ma, Shaodan, Wu, Yik-Chung, Poor, H Vincent. (2014). Distributed Hybrid Power State Estimation Under PMU Sampling Phase Errors. IEEE Transactions on Signal Processing, 62 (16), 4052 - 4063. doi:10.1109/tsp.2014.2332438en_US
dc.identifier.issn1053-587X-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1m61bq07-
dc.description.abstractThis paper proposes a novel distributed reduced-rank scheme and an adaptive algorithm for distributed estimation in wireless sensor networks. The proposed distributed scheme is based on a transformation that performs dimensionality reduction at each agent of the network followed by a reduced-dimension parameter vector. A distributed reduced-rank joint iterative estimation algorithm is developed, which has the ability to achieve significantly reduced communication overhead and improved performance when compared with existing techniques. Simulation results illustrate the advantages of the proposed strategy in terms of convergence rate and mean square error performance.en_US
dc.format.extent4052 - 4063en_US
dc.language.isoen_USen_US
dc.relation.ispartofIEEE Transactions on Signal Processingen_US
dc.rightsAuthor's manuscripten_US
dc.titleDistributed Hybrid Power State Estimation Under PMU Sampling Phase Errorsen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1109/tsp.2014.2332438-
dc.identifier.eissn1941-0476-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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