Parametric estimation in noisy blind deconvolution model: a new estimation procedure

dc.creatorGautherat, Emmanuelle
dc.creatorGayraud, Ghislaine
dc.date2007-11-05
dc.date.accessioned2026-07-07T08:40:40Z
dc.date.available2026-07-07T08:40:40Z
dc.descriptionIn a parametric framework, the paper is devoted to the study of a new estimation procedure for the inverse filter and the level noise in a complex noisy blind discrete deconvolution model. Our estimation method is a consequence of the sharp exploitation of the specifical properties of the Hankel forms. The distribution of the input signal is also estimated. The strong consistency and the asymptotic distribution of all estimates are established. A consistent simulation study is added in order to demonstrate empirically the computational performance of our estimation procedures.
dc.descriptionSubmitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0711.0587
dc.identifierhttp://arxiv.org/abs/0711.0587
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/141438
dc.subjectStatistics Theory
dc.subject62M10, 62F12, 60E07
dc.titleParametric estimation in noisy blind deconvolution model: a new estimation procedure
dc.typetext

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