An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo
Centre National de la Recherche Scientifique · Laboratoire Traitement et Communication de l’Information · +2 more institutions
Abstract
It is now over a decade since the pioneering contribution of Gordon (1993), which is commonly regarded as the first instance of modern sequential Monte Carlo (SMC) approaches. Initially focussed on applications to tracking and vision, these techniques are now very widespread and have had a significant impact in virtually all areas of signal and image processing concerned with Bayesian dynamical models. This paper is intended to serve both as an introduction to SMC algorithms for nonspecialists and as a reference to recent contributions in domains where the techniques are still under significant development, including smoothing, estimation of fixed parameters and use of SMC methods beyond the standard filtering…
Citation impact
- FWCI
- 70.20
- Percentile
- 100%
- References
- 149
Authors
3- OCOlivier CappéCorresponding
Centre National de la Recherche Scientifique, Laboratoire Traitement et Communication de l’Information, Télécom Paris
- SGSimon Godsill
University of Cambridge
- ÉMÉric Moulines
Laboratoire Traitement et Communication de l’Information, Centre National de la Recherche Scientifique, Télécom Paris
Topics & keywords
- Computer science
- Monte Carlo method
- Particle filter
- Smoothing
- Bayesian probability
- Algorithm
- Artificial intelligence
- Kalman filter