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dc.contributor.authorDemirbas, K.en_US
dc.date.accessioned2016-02-08T10:57:13Z
dc.date.available2016-02-08T10:57:13Z
dc.date.issued1989en_US
dc.identifier.issn0020-7721
dc.identifier.urihttp://hdl.handle.net/11693/26255
dc.description.abstractComponent-by-component state smoothing is discussed for multi-dimensional dynamic systems with non-linear random interference such as jamming. Each component of the observation model is a non-linear function of only one state component, arbitrary random interference, and observation noise. Each state component is first approximated by a finite state machine and then, using the Viterbi decoding algorithm of information theory, the state components are sequentially smoothed in parallel. This results in a memory reduction for the implementation of the state smoothing. Simulation results have shown that the proposed scheme performs well, whereas the classical estimation schemes cannot be used, in general, to estimate the states of dynamic models with arbitrary random interference. © 1989 Taylor & Francis Group, LLC.en_US
dc.language.isoEnglishen_US
dc.source.titleInternational Journal of Systems Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1080/00207728908910237en_US
dc.subjectProbability--Random processesen_US
dc.subjectSignal filtering and prediction--Theoryen_US
dc.subjectMultidimensional state smoothingen_US
dc.subjectNonlinear interferenceen_US
dc.subjectRecursive state estimationen_US
dc.subjectViterbi decoding algorithmen_US
dc.subjectMathematical techniquesen_US
dc.titleMulti-dimensional state smoothing in the presence of non-linear interferenceen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage1547en_US
dc.citation.epage1564en_US
dc.citation.volumeNumber20en_US
dc.citation.issueNumber8en_US
dc.identifier.doi10.1080/00207728908910237en_US
dc.publisherTaylor & Francisen_US


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