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Recursive hybrid Cramer-Rao bound for discrete-time Markovian dynamic systems
Article de revue   Open Access   Avec comité de lecture

Recursive hybrid Cramer-Rao bound for discrete-time Markovian dynamic systems

Chengfang Ren, Jérôme Galy, Eric Chaumette, François Vincent, Pascal Larzabal et Alexandre Renaux
IEEE Signal Processing Letters, Vol.22(10), pp.1543-1547
10/2015

Résumé

Dynamic Markovian systems Parameter estimation Estimation error lower bound
In statistical signal processing, hybrid parameter estimation refers to the case where the parameters vector to estimate contains both non-random and random parameters. As a contribution to the hybrid estimation framework, we introduce a recursive hybrid Cramér Rao lower bounds for discrete-time Markovian dynamic systems depending on unknown determinis-tic parameters. Additionnally, the regularity conditions required for its existence and its use are clarified.

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