Population based particle filtering

This paper proposes a novel particle filtering strategy by combining population Monte Carlo Markov chain methods with sequential Monte Carlo chain particle which we call evolving population Monte Carlo Markov Cham (EP MCMC) filtering. Iterative convergence on groups of particles (populations) is obt...

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Veröffentlicht in:	IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications S. 29 - 38
Hauptverfasser:	Bhaskar, H, Mihaylova, L, Maskell, S
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Stevenage IET 2008
Schlagworte:	Filtering methods in signal processing Markov processes Monte Carlo methods Signal processing theory Monte Carlo methods iterative convergence population based particle filtering sequential Monte Carlo chain particle Markov processes particle filtering (numerical methods) Monte Carlo Markov Chain filtering
ISBN:	0863419100, 9780863419102
Online-Zugang:	Volltext
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