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Communication Dans Un Congrès Année : 2011

Optimal SIR algorithm vs. fully adapted auxiliary particle filter : a matter of conditional independence

Résumé

Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse the Sampling Importance Resampling (SIR) PF with optimal conditional importance distribution (CID) and the fully adapted APF (FA-APF). Both algorithms share the same Sampling (S), Weighting (W) and Resampling (R) steps, and only differ in the order in which these steps are performed. The order of the operations is not unsignificant: starting at time n − 1 from a common set of particles, we show that one single updated particle at time n will marginally be sampled in both algorithms from the same probability density function (pdf), but as a whole the full set of particles will be conditionally independent if created by the FA-APF algorithm, and dependent if created by the SIR algorithm, which results in support degeneracy

Dates et versions

hal-01304056 , version 1 (19-04-2016)

Identifiants

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François Desbouvries, Yohan Petetin, Emmanuel Monfrini. Optimal SIR algorithm vs. fully adapted auxiliary particle filter : a matter of conditional independence. ICASSP 2011 : International Conference on Acoustics, Speech and Signal Processing, May 2011, Prague, Czech Republic. pp.3992 - 3995, ⟨10.1109/ICASSP.2011.5947227⟩. ⟨hal-01304056⟩
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