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Volumn 2, Issue , 2005, Pages 1459-1464

Unified framework for sampling/importance resampling algorithms

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA COMPRESSION; KALMAN FILTERS; MONTE CARLO METHODS;

EID: 33847120406     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIF.2005.1592027     Document Type: Conference Paper
Times cited : (10)

References (14)
  • 2
    • 0027580559 scopus 로고
    • Novel approach to nonlinear/non-Gaussian Bayesian state estimation
    • April
    • N. J. Gordon, D. J. Salmond, and A. F. M. Smith, "Novel approach to nonlinear/non-Gaussian Bayesian state estimation," IEE Proceedings F, vol. 140, no. 2, April 1993.
    • (1993) IEE Proceedings F , vol.140 , Issue.2
    • Gordon, N.J.1    Salmond, D.J.2    Smith, A.F.M.3
  • 6
    • 0036504051 scopus 로고    scopus 로고
    • A survey of convergence results on particle filtering methods for practitioners
    • March
    • D. Crisan and A. Doucet, "A survey of convergence results on particle filtering methods for practitioners," IEEE Transactions on signal processing, vol. 50, no. 3, March 2002.
    • (2002) IEEE Transactions on signal processing , vol.50 , Issue.3
    • Crisan, D.1    Doucet, A.2
  • 8
    • 0036475447 scopus 로고    scopus 로고
    • A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
    • February
    • S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Transactions on signal processing, vol. 50, no. 2, February 2002.
    • (2002) IEEE Transactions on signal processing , vol.50 , Issue.2
    • Arulampalam, S.1    Maskell, S.2    Gordon, N.3    Clapp, T.4
  • 9
    • 84947876691 scopus 로고    scopus 로고
    • A. Doucet, On sequential simulation-based methods for Bayesian filtering, Signal Processing Group, Department of Engineering, University of Cambridge, Tech. Rep. CUED/F-INFENG/TR 310, 1998.
    • A. Doucet, "On sequential simulation-based methods for Bayesian filtering," Signal Processing Group, Department of Engineering, University of Cambridge, Tech. Rep. CUED/F-INFENG/TR 310, 1998.
  • 12
    • 0008782869 scopus 로고    scopus 로고
    • Improvement strategies for Monte Carlo particle filters
    • A. Doucet, N. de Freitas, and N. Gordon, Eds. New York: Springer-Verlag, ch. 7, pp
    • S. Godsill and T. Clapp, "Improvement strategies for Monte Carlo particle filters," in Sequential Monte Carlo in Practice, A. Doucet, N. de Freitas, and N. Gordon, Eds. New York: Springer-Verlag, 2001, ch. 7, pp. 139 - 158.
    • (2001) Sequential Monte Carlo in Practice , pp. 139-158
    • Godsill, S.1    Clapp, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.