Recursive Hybrid Cramér-Rao Bound for Discrete-Time Markovian Dynamic Systems

Recursive Hybrid Cramér-Rao Bound for Discrete-Time Markovian Dynamic Systems

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 bound for discrete-time Mar...

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Veröffentlicht in:IEEE signal processing letters 2015-10, Vol.22 (10), p.1543-1547
Hauptverfasser: Chengfang Ren, Galy, Jerome, Chaumette, Eric, Vincent, Francois, Larzabal, Pascal, Renaux, Alexandre
Format: Artikel
Sprache:eng
Schlagworte:
Bayes methods
Computer Science
dynamic Markovian systems
Electronic mail
Estimation
estimation error lower bound
Indexes
Noise
Parameter estimation
Signal and Image Processing
Vectors
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Beschreibung
Zusammenfassung: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 bound for discrete-time Markovian dynamic systems depending on unknown deterministic parameters. Additionally, the regularity conditions required for its existence and its use are clarified.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2015.2412173