Particle Filter

Particle filter methods, also known as Sequential Monte Carlo (SMC), are sophisticated model estimation techniques based on simulation. They are usually used to estimate Bayesian models and are the sequential ('on-line') analogue of Markov Chain Monte Carlo (MCMC) batch methods.

See also

References

  • Sequential Monte Carlo Methods in Practice, by A Doucet, N de Freitas and N Gordon. Published by Springer.
  • Tutorial on Particle Filters for On-line Nonlinear/Non-Gaussian Bayesian Tracking (2001); S. Arulampalam, S. Maskell, N. Gordon and T. Clapp; CiteSeer link

 

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