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dc.date.accessioned 2019-06-21T16:17:30Z
dc.date.available 2019-06-21T16:17:30Z
dc.date.issued 2013
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/76852
dc.description.abstract Multiple damped complex exponentials are of great practical importance as they are useful for describing many technological situations. Several estimators have been developed for the parameters of these complex exponentials. In this paper, we apply the MiniMax affine estimator to this problem in order to obtain a better performance (in terms of the mean squared error) than other unbiased estimators. Through simulations, this estimator is shown to have a reduced mean squared error, especially for the adverse case of lower signal-to-noise ratio. Additionally, a closed form expression for the MiniMax affine estimator is presented. en
dc.format.extent 81-92 es
dc.language en es
dc.subject damped sinusoids estimation en
dc.subject affine estimators en
dc.subject mean squared error en
dc.title MiniMax Affine Estimation of Parameters of Multiple Damped Complex Exponentials en
dc.type Objeto de conferencia es
sedici.identifier.uri http://42jaiio.sadio.org.ar/proceedings/simposios/Trabajos/AST/08.pdf es
sedici.identifier.issn 1850-2806 es
sedici.creator.person Gama, Fernando es
sedici.creator.person Casaglia, Daniel es
sedici.creator.person Cernuschi-Frías, Bruno es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Sociedad Argentina de Informática e Investigación Operativa es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.date.exposure 2013-09
sedici.relation.event XIV Argentine Symposium on Technology (AST) - JAIIO 42 (2013) es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)