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Volumn 2005, Issue , 2005, Pages 64-69

Comparison of resampling schemes for particle filtering

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS;

EID: 33746863594     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ispa.2005.195385     Document Type: Conference Paper
Times cited : (790)

References (19)
  • 3
    • 21644457738 scopus 로고    scopus 로고
    • Central limit theorem for sequential monte carlo methods and its application to bayesian inference
    • N. Chopin. Central limit theorem for sequential monte carlo methods and its application to bayesian inference. Ann. Statist., 32(6):2385-2411, 2004.
    • (2004) Ann. Statist. , vol.32 , Issue.6 , pp. 2385-2411
    • Chopin, N.1
  • 4
    • 0001524126 scopus 로고    scopus 로고
    • Discrete filtering using branching and interacting particle systems
    • D. Crisan, P. Del Moral, and T. Lyons. Discrete filtering using branching and interacting particle systems. Markov Process. Related Fields, 5(3):293-318, 1999.
    • (1999) Markov Process. Related Fields , vol.5 , Issue.3 , pp. 293-318
    • Crisan, D.1    Del Moral, P.2    Lyons, T.3
  • 7
    • 0003665481 scopus 로고    scopus 로고
    • A. Doucet, N. De Freitas, and N. Gordon, editors Springer, New York
    • A. Doucet, N. De Freitas, and N. Gordon, editors. Sequential Monte Carlo Methods in Practice. Springer, New York, 2001.
    • (2001) Sequential Monte Carlo Methods in Practice
  • 10
    • 0242550819 scopus 로고    scopus 로고
    • On-line inference for hidden Markov models via particle filters
    • P. Fearnhead and P. Clifford. On-line inference for hidden Markov models via particle filters. J. Roy. Statist. Soc. Ser. B, 65:887-899, 2003.
    • (2003) J. Roy. Statist. Soc. Ser. B , vol.65 , pp. 887-899
    • Fearnhead, P.1    Clifford, P.2
  • 11
    • 0027580559 scopus 로고
    • Novel approach to nonlinear/non-Gaussian Bayesian state estimation
    • N. Gordon, D. Salmond, and A. F. Smith. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proc. F, Radar Signal Process., 140:107-113, 1993.
    • (1993) IEE Proc. F, Radar Signal Process. , vol.140 , pp. 107-113
    • Gordon, N.1    Salmond, D.2    Smith, A.F.3
  • 12
    • 84874286884 scopus 로고
    • Monte Carlo techniques to estimate the conditionnal expectation in multi-stage non-linear filtering
    • J. Handschin and D. Mayne. Monte Carlo techniques to estimate the conditionnal expectation in multi-stage non-linear filtering. In Int. J. Control, volume 9, pages 547-559, 1969.
    • (1969) Int. J. Control , vol.9 , pp. 547-559
    • Handschin, J.1    Mayne, D.2
  • 13
    • 0030304310 scopus 로고    scopus 로고
    • Monte-Carlo filter and smoother for non-Gaussian nonlinear state space models
    • G. Kitagawa. Monte-Carlo filter and smoother for non-Gaussian nonlinear state space models. J. Comput. Graph. Statist., 1:1-25, 1996.
    • (1996) J. Comput. Graph. Statist. , vol.1 , pp. 1-25
    • Kitagawa, G.1
  • 16
    • 0002174025 scopus 로고
    • A solution of the smoothing problem for linear dynamic systems
    • D. Q. Mayne. A solution of the smoothing problem for linear dynamic systems. Automatica, 4:73-92, 1966.
    • (1966) Automatica , vol.4 , pp. 73-92
    • Mayne, D.Q.1
  • 19
    • 0002338687 scopus 로고
    • A genetic algorithm tutorial
    • D. Whitley. A genetic algorithm tutorial. Stat. Comput., 4:65-85, 1994.
    • (1994) Stat. Comput. , vol.4 , pp. 65-85
    • Whitley, D.1


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