An iterative implementation of the implicit nonlinear filter

Alexandre J. Chorin; Xuemin Tu

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique (2012)

  • Volume: 46, Issue: 3, page 535-543
  • ISSN: 0764-583X

Abstract

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Implicit sampling is a sampling scheme for particle filters, designed to move particles one-by-one so that they remain in high-probability domains. We present a new derivation of implicit sampling, as well as a new iteration method for solving the resulting algebraic equations.

How to cite

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Chorin, Alexandre J., and Tu, Xuemin. "An iterative implementation of the implicit nonlinear filter." ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique 46.3 (2012): 535-543. <http://eudml.org/doc/273153>.

@article{Chorin2012,
abstract = {Implicit sampling is a sampling scheme for particle filters, designed to move particles one-by-one so that they remain in high-probability domains. We present a new derivation of implicit sampling, as well as a new iteration method for solving the resulting algebraic equations.},
author = {Chorin, Alexandre J., Tu, Xuemin},
journal = {ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique},
keywords = {implicit sampling; filter; reference density; jacobian; iteration; particles; Jacobian},
language = {eng},
number = {3},
pages = {535-543},
publisher = {EDP-Sciences},
title = {An iterative implementation of the implicit nonlinear filter},
url = {http://eudml.org/doc/273153},
volume = {46},
year = {2012},
}

TY - JOUR
AU - Chorin, Alexandre J.
AU - Tu, Xuemin
TI - An iterative implementation of the implicit nonlinear filter
JO - ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique
PY - 2012
PB - EDP-Sciences
VL - 46
IS - 3
SP - 535
EP - 543
AB - Implicit sampling is a sampling scheme for particle filters, designed to move particles one-by-one so that they remain in high-probability domains. We present a new derivation of implicit sampling, as well as a new iteration method for solving the resulting algebraic equations.
LA - eng
KW - implicit sampling; filter; reference density; jacobian; iteration; particles; Jacobian
UR - http://eudml.org/doc/273153
ER -

References

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  12. [12] J. Liu and C. Sabatti, Generalized Gibbs sampler and multigrid Monte Carlo for Bayesian computation. Biometrika87 (2000) 353–369. Zbl0960.65015MR1782484
  13. [13] S. Maceachern, M. Clyde and J. Liu, Sequential importance sampling for nonparametric Bayes models : the next generation. Can. J. Stat.27 (1999) 251–267. Zbl0957.62068MR1704407
  14. [14] M. Morzfeld, X. Tu, E. Atkins and A.J. Chorin, A random map implementation of implicit filters. Submitted to J. Comput. Phys. Zbl1242.65012
  15. [15] C. Snyder, T. Bengtsson, P. Bickel and J. Anderson, Obstacles to high-dimensional particle filtering. Mon. Weather Rev.136 (2008) 4629–4640. 

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