23 citations · 58 across the 10 of their papers we have counts for
4 papers · 1 filter
Semi-independent resampling for particle filtering
Roland Lamberti, Yohan Petetin, François Desbouvries +1
Among Sequential Monte Carlo (SMC) methods,Sampling Importance Resampling (SIR) algorithms are based on Importance Sampling (IS) and on some resampling-based)rejuvenation algorithm…
Independent Resampling Sequential Monte Carlo Algorithms
Roland Lamberti, Yohan Petetin, François Desbouvries +1
Sequential Monte Carlo algorithms, or Particle Filters, are Bayesian filtering algorithms which propagate in time a discrete and random approximation of the a posteriori distributi…
A class of fast exact Bayesian filters in dynamical models with jumps
Yohan Petetin, François Desbouvries
In this paper, we focus on the statistical filtering problem in dynamical models with jumps. When a particular application relies on physical properties which are modeled by linear…
Bayesian Conditional Monte Carlo Algorithms for Sequential Single and Multi-Object filtering
Yohan Petetin, François Desbouvries
Bayesian filtering aims at tracking sequentially a hidden process from an observed one. In particular, sequential Monte Carlo (SMC) techniques propagate in time weighted trajectori…