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A hybrid lower bound for parameter estimation of signals with multiple change-points

Bacharach, Lucien and El-Korso, Mohammed Nabil and Renaux, Alexandre and Tourneret, Jean-Yves A hybrid lower bound for parameter estimation of signals with multiple change-points. (2019) IEEE Transactions on Signal Processing, 67 (5). 1267-1279. ISSN 1053-587X

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Official URL: https://doi.org/10.1109/TSP.2018.2890029


Change-point estimation has received much attention in the literature as it plays a significant role in several signal pro- cessing applications. However, the study of the optimal estimation performance in such context is a difficult task since the unknown parameter vector of interest may contain both continuous and dis- crete parameters, namely the parameters associated with the noise distribution and the change-point locations. In this paper, we han- dle this by deriving a lower bound on the mean square error of these continuous and discrete parameters. Specifically, we propose a hybrid Crame ́r–Rao–Weiss-Weinstein bound and derive its as- sociated closed-form expressions. Numerical simulationsassess the tightness of the proposed bound in the case of Gaussian and Poisson observations.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Ecole Supérieure d'Electricité - SUPELEC (FRANCE)
Other partners > Université Paris-Saclay (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Other partners > Université Paris Ouest Nanterre La Défense (FRANCE)
Laboratory name:
Agence Nationale de la Recherche - ANR (FRANCE)
Deposited On:06 Feb 2019 10:31

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