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dc.date.accessioned 2021-08-31T13:21:25Z
dc.date.available 2021-08-31T13:21:25Z
dc.date.issued 2012
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/123804
dc.description.abstract Affine estimation has emerged as a promising technique to reduce the mean squared error (MSE) between the estimated parameters and the true value of these parameters. The aim of this paper is to obtain an affine estimator for the frequency of a complex sinusoid corrupted by white gaussian noise. Additionally, an adaptive technique is presented. The simulation results clearly show that affine estimators have better performance than unbiased estimators such as the maximum likelihood estimator (MLE) and the Fu-Kam approximation. en
dc.format.extent 121-131 es
dc.language en es
dc.subject Single Tone Estimation es
dc.subject Affine Estimators es
dc.subject Mean Squared Error es
dc.subject Adaptive Algorithm es
dc.title Application of Affine Estimators to Single Tone Frequency Estimation en
dc.type Objeto de conferencia es
sedici.identifier.uri https://41jaiio.sadio.org.ar/sites/default/files/11_AST_2012.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 2012-08
sedici.relation.event XIII Argentine Symposium on Technology (AST 2012) (XLII JAIIO, La Plata, 27 y 28 de agosto de 2012) 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)