Parametric estimation for a signal-plus-noise model from discrete time observations

Abstract : This paper deals with the parametric inference for integrated signals embedded in an additive Gaussian noise and observed at deterministic discrete instants which are not necessarily equidistant. The unknown parameter is multidimensional and compounded of a signal-of-interest parameter and a variance parameter of the noise. We state the consistency and the minimax efficiency of the maximum likelihood estimator and of the Bayesian estimator when the time of observation tends to ∞ and the delays between two consecutive observations tend to 0 or are only bounded. The class of signals in consideration contains among others, almost periodic signals and also non-continuous periodic signals. However the problem of frequency estimation is not considered here.
Type de document :
Pré-publication, Document de travail
Liste complète des métadonnées
Contributeur : Dominique Dehay <>
Soumis le : jeudi 14 mars 2019 - 12:02:21
Dernière modification le : dimanche 17 mars 2019 - 01:13:41


Fichiers produits par l'(les) auteur(s)


  • HAL Id : hal-02067554, version 1
  • ARXIV : 1903.06447


Dominique Dehay, Khalil El Waled, Vincent Monsan. Parametric estimation for a signal-plus-noise model from discrete time observations. 2019. ⟨hal-02067554⟩



Consultations de la notice


Téléchargements de fichiers