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dc.contributor.authorKerestecioǧlu, Feza
dc.contributor.authorCetin, I
dc.date.accessioned2019-06-27T08:00:55Z
dc.date.available2019-06-27T08:00:55Z
dc.date.issued2004
dc.identifier.issn0020-7721
dc.identifier.urihttps://hdl.handle.net/20.500.12469/160
dc.identifier.urihttps://dx.doi.org/10.1080/00207720410001734219
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/00207720410001734219
dc.description.abstractThe effects of auxiliary input signals on detecting changes in ARMAX processes via statistical tests are discussed. Two extensions to the Cumulative Sum Test are considered. The first is applicable when the direction of the change in the parameter space is known but its magnitude is unknown. The second is applicable when neither is known. The performance criteria for the design of stationary stochastic inputs are based on the asymptotic properties of the tests. It is shown that power-constrained optimal inputs have discrete spectra and a suitably chosen input can greatly improve the detection performance.
dc.language.isoEnglish
dc.publisherTaylor & Francis Ltd
dc.titleOptimal input design for the detection of changes towards unknown hypotheses
dc.typeArticle
dc.identifier.startpage435
dc.identifier.endpage444
dc.relation.journalInternational Journal of Systems Science
dc.identifier.issue7
dc.identifier.volume35
dc.identifier.wosWOS:000223474800004
dc.identifier.doi10.1080/00207720410001734219
dc.contributor.khasauthorKerestecioǧlu, Feza


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