Optimisation of particle filters using simultaneous perturbation stochastic approximation

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 6, Issue , 2003, Pages 681-684

  Chan, Bao Ling ^a   Doucet, Arnaud ^b   Tadic, Vladislav B ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; MONTE CARLO METHODS; OPTIMIZATION; PERTURBATION TECHNIQUES;

PARTICLE FILTERS;

SIGNAL FILTERING AND PREDICTION;

EID: 0141853953     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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2. A. Doucet, and V.B. Tadić", "On-line optimization of sequential Monte Carlo methods using stochastic approximation", Proc. American Control Conference, May 2002.
3. V.B. Tadić, and A. Doucet, "Exponential forgetting and geometric ergodicity in general state-space models", Proc. IEEE Conference Decision and Control, December 2002.
4. J.C. Spall, "An overview of the simultaneous perturbation method for efficient optimisation," John Hopkin Technical Digest, vol. 19, no. 4, pp. 482-492, 1998.
5. D. Crisan, and A. Doucet, "A survey of convergence results on particle filtering for practitioners", IEEE Trans. Signal Processing, vol. 50, no. 3, pp. 736-746, 2002.
6. J.C. Spall, "Implementation of the simultaneous perturbation algorithm for stochastic optimisation", IEEE Trans. Aerospace and Electronic Systems, vol. 34, no. 3, 1998.
7. N.L. Kleinman, J.C. Spall and D.Q. Naiman, "Simulation-based optimisation with stochastic approximation using common random numbers", Management Science, vol. 45, no. 11, pp. 1570-1578, 1999.
8. G. Kitagawa, "Monte Carlo filter and smoother for non-Gaussian nonlinear state space models", J. Comput. Graph. Statist., vol. 5, pp. 1-25, 1996.