Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/104993
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dc.titleAn efficient algorithm for estimating the parameters of superimposed exponential signals
dc.contributor.authorBai, Z.D.
dc.contributor.authorRao, C.R.
dc.contributor.authorChow, M.
dc.contributor.authorKundu, D.
dc.date.accessioned2014-10-28T05:09:58Z
dc.date.available2014-10-28T05:09:58Z
dc.date.issued2003-01-15
dc.identifier.citationBai, Z.D.,Rao, C.R.,Chow, M.,Kundu, D. (2003-01-15). An efficient algorithm for estimating the parameters of superimposed exponential signals. Journal of Statistical Planning and Inference 110 (1-2) : 23-34. ScholarBank@NUS Repository.
dc.identifier.issn03783758
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104993
dc.description.abstractAn efficient computational algorithm is proposed for estimating the parameters of undamped exponential signals, when the parameters are complex valued. Such data arise in several areas of applications including telecommunications, radio location of objects, seismic signal processing and computer assisted medical diagnostics. It is observed that the proposed estimators are consistent and the dispersion matrix of these estimators is asymptotically the same as that of the least squares estimators. Moreover, the asymptotic variances of the proposed estimators attain the Cramer-Rao lower bounds, when the errors are Gaussian. © 2001 Elsevier Science B.V.
dc.sourceScopus
dc.subjectCramer-Rao lower bound
dc.subjectEquivariance linear prediction
dc.subjectForward and backward linear prediction
dc.subjectMaximum likelihood estimators
dc.subjectSuperimposed exponential signals
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.sourcetitleJournal of Statistical Planning and Inference
dc.description.volume110
dc.description.issue1-2
dc.description.page23-34
dc.description.codenJSPID
dc.identifier.isiutNOT_IN_WOS
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