M. Bolic, P. M. Djuric, and S. Hong, Resampling algorithms for particle filters: A computational complexity perspective, EURASIP Journal on Applied Signal Processing, vol.15, pp.2267-2277, 2004.

O. Cappé, R. Douc, and E. Moulines, Comparaison of resampling schemes for particle filtering, 4th ISPA, 2005.

F. Cérou, F. Legland, and N. J. Newton, Stochastic particle methods for linear tangent filtering equations, pp.231-240, 2001.

B. L. Chan, A. Doucet, and V. B. Tadic, Optimisation of particle filters using simultaneous perturbation stochastic approximation, ICASSP, pp.681-685, 2003.

N. Chopin, Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference, The Annals of Statistics, vol.32, issue.6, pp.2385-2411, 2004.
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D. Crisan and A. Doucet, A survey of convergence results on particle filtering methods for practitioners, IEEE Transactions on Signal Processing, vol.50, issue.3, pp.736-746, 2002.
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R. Douc, A. Guillin, and J. Najim, Moderate deviations for particle filtering, The Annals of Applied Probability, vol.15, issue.1B, pp.587-614, 2004.
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R. Douc and C. Matias, Asymptotics of the Maximum Likelihood Estimator for General Hidden Markov Models, Bernoulli, vol.7, issue.3, pp.381-420, 2001.
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R. Douc and E. Moulines, Limit theorems for weighted samples with applications to sequential monte carlo methods, Ann. Appl. Probab, 2006.
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A. Doucet, N. De-freitas, and M. Klaas, Toward practicle n 2 monte carlo: the marginal particle filter, ICML, 2005.

A. Doucet, N. De-freitas, K. Murphy, and S. Russell, Raoblackwellised particle filtering for dynamic bayesian networks, 16th CUAI, pp.176-183, 2000.

A. Doucet, N. D. Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice, 2001.
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A. Doucet and S. Godsill, On sequential monte carlo sampling methods for bayesian filtering, Statistics and Computing, vol.10, issue.3, pp.197-208, 2000.
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A. Doucet and V. B. Tadic, Parameter estimation in general statespace models using particle methods, Ann. Inst. Stat. Math, 2003.

J. Fichoud, F. Legland, and L. Mevel, Particle-based methods for parameter estimation and tracking : numerical experiments, 2003.

A. Guyader, F. Legland, and N. Oudjane, A particle implementation of the recursive mle for partially observed diffusions, 13th IFAC Symposium on System Identification, pp.1305-1310, 2003.
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P. and D. Moral, Feynman-Kac Formulae Genealogical and Interacting Particle Systems with Applications, 2004.

P. , D. Moral, and L. Miclo, Branching and interacting particle systems . approximations of feynman-kac formulae with applications to non-linear filtering, pp.1-145, 2000.

G. Poyadjis, A. Doucet, and S. S. Singh, Particle Methods for Optimal Filter Derivative: Application to Parameter Estimation, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2005.
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G. Poyiadjis, Particle Method for Parameter Estimation in General State Space Models, 2006.

G. Poyiadjis, S. S. Singh, and A. Doucet, Particle Filter as A Controlled Markov Chain For On-Line Parameter Estimation in General State Space Models, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006.
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