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dc.contributor.authorXuehai Wang
dc.contributor.authorFang Zhu
dc.contributor.otherSchool of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, China
dc.contributor.otherSchool of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, China
dc.date.accessioned2025-08-27T02:32:33Z
dc.date.accessioned2025-10-08T08:07:14Z
dc.date.available2025-10-08T08:07:14Z
dc.date.issued2025-07
dc.identifier.urihttps://www.aimspress.com/article/doi/10.3934/math.2025760
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/35635
dc.description.abstractThe censored measurements are unavoidably encountered in practical scenarios due to sudden changes of circumstances and physical constraints, and the traditional parameter and state estimation methods may result in obvious estimation bias and serious performance degradation when the collected measurements contain censored observations. This paper concerns the synchronous parameter and state estimation for the bilinear state-space systems with censored measurements. By compensating the estimation bias from the censored measurements and constructing a novel criterion function, a censored regression-based gradient method is presented for synchronously estimating the system parameters and states. Moreover, a censored regression-based multi-innovation gradient method is derived to enhance the estimation performance. Theoretical analysis reveals that the convergence of the parameter estimates can be guaranteed under the persistent excitation condition. The simulation examples exhibit that the proposed method performs significantly better than the conventional auxiliary model-based least mean square method.
dc.language.isoEN
dc.publisherAIMS Press
dc.subject.lccMathematics
dc.titleSynchronous parameter and state estimation for bilinear state-space systems with censored measurements
dc.typeArticle
dc.description.keywordsparameter estimation
dc.description.keywordsstate estimation
dc.description.keywordsbilinear state-space system
dc.description.keywordsbias compensation
dc.description.keywordscensored measurement
dc.description.pages16898-16926
dc.description.doi10.3934/math.2025760
dc.title.journalAIMS Mathematics
dc.identifier.e-issn2473-6988
dc.identifier.oaie64e45607d6941648500787af9efa815
dc.journal.infoVolume 10, Issue 7


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